Publications






Année 2020:

Revues

  1. Maruyama, T.M., Oliveira, L.S., Britto, A.S. and Sabourin, R. Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation,, IEEE Transactions on Information Forensics and Security, October 2020. 

     
  2. Zyblewski, P., Sabourin, R. and Wozniak, M. Preprocessed Dynamic Classifier Ensemble Selection for Highly Imbalanced Drifted Data Streams, Information Fusion, vol 66, February 2021, pp 138-154. 

     
  3. Silva, R.A., Britto. A.S., Enembreck, F., Sabourin, R. and Oliveira, L.S. Selecting and combining classifiers based on Centrality Measures, International Journal on Artificial Intelligence Tools, April, 2020. 

     
  4. Souza, V.L.F., Oliveira, A.L.I., Cruz, R.M.O. and Sabourin, R. A White-Box Analysis on the Writer-Independent Dichotomy Transformation Applied to Offline Handwritten Signature Verification, Expert Systems with Applications, March 2020 (Accepted). 

     
  5. R. M. O. Cruz, L. G. Hafemann, R. Sabourin, and G. D. C. Cavalcanti, DESlib: A dynamic ensemble selection library in python, Journal of Machine Learning Research, vol. 21, No. 8, February 2020, pp. 1-5.  (github

     
  6. R. Soleymani, E. Granger, G. Fumera, F-measure curves: A tool to visualize classifier performance under imbalance, submitted to Journal of Pattern Recognition, January 2020. 

     
  7. F. Mokhayeri, E. Granger A paired sparse representation model for robust face recognition from a single sample, submitted to Journal of Pattern Recognition, January 2020 (Accepted Jan 2020). 

     
  8. Hafemann, L.G., Sabourin, R., and Oliveira L.S., Meta-learning for fast classifier adaptation to new users of Signature Verification systems, IEEE Transactions on Information Forensics & Security, Vol 15, No 1, December 2020, pp 1735-1745. 

     
Conferences

  1. Monteiro, M., Britto Jr, A., Barddal, Oliveira L.S., and Sabourin, R. Classifier Pool Generation based on a Two-level Diversity Approach, 25th International Conference on Pattern Recognition (ICPR 2020), Milan, Italy, 10-15 January 2021.

     
  2. Souza, V.L.F., Oliveira, A.L.I., Cruz, R.M.O. and Sabourin, R. An Investigation of Feature Selection and Transfer Learning for Writer-Independent Offline Handwritten Signature Verification, 25th International Conference on Pattern Recognition (ICPR 2020), Milan, Italy, 10-15 January 2021.

     
  3. Malik Boudiaf, Jérôme Rony, Imtiaz Masud Ziko, Eric Granger, Marco Pedersoli, Pablo Piantanida, Ismail Ben Ayed A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses, European Conference on Computer Vision (ECCV 2020), Glasgow, UK, August 23-28, 2020.

     
  4. Djebril Mekhazni, Amran Bhuiyan, George Ekladious, Eric Granger Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification, European Conference on Computer Vision (ECCV 2020), Glasgow, UK, August 23-28, 2020.

     
  5. Cao, H., Bernard, S., Sabourin, R. and Heutte, L. A Novel Random Forest Dissimilarity Measure for Multi-View Learning, 25th International Conference on Pattern Recognition (ICPR 2020), Milan, Italy, 10-15 January 2021. 

     
  6. Coetzer, J., Swanepoel, J. and Sabourin, R.,Dynamic Fusion of Human and Machine Decisions for Efficient Cost-Sensitive Biometric Authentication, International SAUPEC-RobMech-PRASA Conference, Cape Town, South Africa, January 29-31, 2020.

     
  7. Souza, V.L.F., Oliveira, A.L.I., Cruz, R.M.O. and Sabourin, R.,Improving BPSO-based feature selection applied to offline WI handwritten signature verification through overfitting control, The Genetic and Evolutionary Computation Conference (GECCO-2020), Cancun, Mexico, July 8-12, 2020.

     
  8. Souza, M.A., Sabourin, R., Cavalcanti, G.D.C. and Cruz, R.M.O.,Multi-label learning for dynamic model type recommendation, 2020 International Joint Conference on Neural Networks (IJCNN-2020), Glasgow, UK, July 19-24, 2020.

     
  9. Hochuli, A.G., Britto Jr, A., Barddal, Oliveira L.S., and Sabourin, R.,An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings, 2020 International Joint Conference on Neural Networks (IJCNN-2020), Glasgow, UK, July 19-24, 2020. 

     
  10. Fania Mokhayeri, Kaveh Kamali, Eric Granger Cross-Domain Face Synthesis using a Controllable GAN, 2020 Winter Conference on Applications of Computer Vision (WACV) 

     



  11. Année 2019:

    Revues

    1. Saman Bashbaghi, Eric Granger, Robert Sabourin, Mostafa Parchami Deep Learning Architectures for Face Recognition in Video Surveillance, Deep Learning in Object Detection and Recognition pp 133-154 Nov 2019 

       
    2. Zaag, M., Botez, R. M., & Wong, T. CESSNA citation X engine model identification using neural networks and extended great deluge algorithms.,INCAS Bulletin, 11(2), 195-207, 2019 

       
    3. Li Wang,Senior Member, IEEE,DongNie, Guannan Li, Élodie Puybareau, Jose Dolz, Qian Zhang,Fan Wang, Jing Xia, Zhengwang Wu, Jia-Wei Chen,Member, IEEE, Kim-Han Thung, Toan Duc Bui,Jitae Shin, Guodong Zeng, Guoyan Zheng,Member, IEEE, Vladimir S. Fonov, Andrew Doyle,Yongchao Xu, Pim Moeskops, Josien P. W. Pluim,Fellow, IEEE, Christian Desrosiers,Ismail Ben Ayed, Gerard Sanroma, Oualid M. Benkarim, Adrià Casamitjana,Verónica Vilaplana, Weili Lin, Gang Li,Senior Member, IEEE,and Dinggang Shen,Fellow, IEEE Benchmark on automatic six-month-old infant brain segmentation algorithms: the iSeg-2017 challenge,IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 9, SEPTEMBER 2019 

       
    4. Mohamed Mhiri and Christian Desrosiers and Mohamed Cheriet Word spotting and recognition via a joint deep embedding of image and text,Pattern Recognition Volume 88, April 2019, Pages 312-320 

       
    5. Soufiane Belharbi, Ismail Ben Ayed, Luke McCaffrey, Eric Granger Deep Ordinal Classification with Inequality Constraints, published to CoRR, Nov 2019 

       
    6. Vriesman, D., Britto, A. S., Zimmer, A., Koerich, A. L., & Paludo, R. Automatic visual inspection of thermoelectric metal pipes, Signal, Image and Video Processing, 13(5), 975-983. July 2019 

       
    7. Fania Mokhayeri, Eric Granger Video Face Recognition Using Siamese Networks with Block-Sparsity Matching, IEEE TRANSACTION ON BIOMETRICS, BEHAVIOR, AND IDENTITY SCIENCE, Oct 2019 

       
    8. Esmaeilpour, M., Cardinal, P., & Koerich, A. L. Unsupervised feature learning for environmental sound classification using cycle consistent generative adversarial network., Paper Accepted for Publication in Applied Soft Computing, November 2019  

       
    9. Jérôme Rony, Soufiane Belharbi, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, Eric Granger Deep weakly-supervised learning methods for classification and localization in histology images: a survey, published to CoRR ,Sept 2019 

       
    10. Masih Aminbeidokhti, Marco Pedersoli, Patrick Cardinal, Eric Granger Emotion Recognition with Spatial Attention and Temporal Softmax Pooling, Image Analysis and Recognition, Jul 2019 

       
    11. Juan D. S. Ortega, Mohammed Senoussaoui, Eric Granger, Marco Pedersoli, Patrick Cardinal, Alessandro L. Koerich Multimodal Fusion with Deep Neural Networks for Audio-VideoEmotion Recognition, Jul 2019 

       
    12. Akhil Meethal, Marco Pedersoli, Soufiane Belharbi, Eric Granger Convolutional STN for Weakly Supervised Object Localization and Beyond, published to CoRR Dec 2019 

       
    13. A Chaddad, M Toews, C Desrosiers, T Niazi Deep radiomic analysis based on modeling information flow in convolutional neural networks, IEEE Access Jul 2019 

       
    14. Majid Masoumi, Matthew Toews, and Hervé Lombaert WaveletBrain: Characterization of human brain viaspectral graph wavelets, Jul 2019 

       
    15. Sajjad Abdoli, Luiz G. Hafemann, Jérome Rony, Ismail Ben Ayed, Patrick Cardinal and Alessandro L.Koerich Universal Adversarial Audio Perturbations, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE Nov 2019 

       
    16. Saypraseuth Mounsaveng, David Vazquez, Ismail Ben Ayed, Marco Pedersoli Adversarial Learning of General Transformations for Data Augmentation, Sept 2019 

       
    17. Li Wang,Senior Member, IEEE,DongNie, Guannan Li, Élodie Puybareau, Jose Dolz, Qian Zhang,Fan Wang, Jing Xia, Zhengwang Wu, Jia-Wei Chen Benchmark on Automatic Six-Month-Old InfantBrain Segmentation Algorithms: TheiSeg-2017 Challenge, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 9, SEPTEMBER 2019 

       
    18. Hugo Masson, Amran Bhuiyan, Le Thanh Nguyen-Meidine, Mehrsan Javan, Parthipan Siva, Ismail Ben Ayed, Eric Granger A Survey of Pruning Methods for Efficient Person Re-identification Across Domains, preprint 

       
    19. Silva, R.A., Britto. A.S., Enembreck, F., Sabourin, R. and Oliveira, L.S., CSBF: A Static Ensemble Fusion Method based on Centrality Score of Complex Networks, Computational Intelligence, October 2019 (Accepted). 

       
    20. Hafemann, L.G., Oliveira L.S. and Sabourin, R., Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification, IEEE Transactions on Information Forensics & Security, Vol. 14, No. 8, August 2019, pp 2153-2166. 

       
    21. Cao, H., Bernard, S., Sabourin, R. and Heutte, L, Random Forest Dissimilarity Based Multi-View Learning for Radiomics Application, Pattern Recognition, Vol. 88, April 2019, pp 185-197. 

       
    22. Souza, M., Cavalcanti, G.D.C., Cruz, M.O.R. and Sabourin, R., Online Local Pool Generation for Dynamic Classifier Selection, Pattern Recognition, Vol. 85, January 2019, pp 132-148. 

       
    23. Cruz, M.O.R., Oliveira, D., Cavalcanti, G.D.C. and Sabourin, R., FIRE-DES++: Enhanced Online Pruning of Base Classifiers for Dynamic Ensemble Selection, Pattern Recognition, Vol. 85, January 2019, pp 149-160. 

       
    24. H Kervadec, J Dolz, M Tang, E Granger, Y Boykov, IB Ayed, Constrained-CNN losses for weakly supervised segmentation, Medical Image Analysis 54, 88-99, 2019. 

       
    25. MA Carbonneau, E Granger, G Gagnon, Bag-Level Aggregation for Multiple Instance Active Learning in Instance Classification Problems, IEEE Transactions on Neural Networks and Learning Systems 30 (5), 1441-1451, 2019. 

       
    26. F Mokhayeri, E Granger, GA Bilodeaun, Domain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per Person, IEEE Transactions on Information Forensics & Security 14 (3), 757-772, 2019. 

       
    27. M. Esmailpour, P. Cardinal, A.L. Koerich. A Robust Approach for Securing Audio Classification Against Adversarial Attacks. IEEE Transactions on Information Forensics and Security. Accepted for Publication. November 2019. 

       
    28. M. Esmailpour, P. Cardinal, A.L. Koerich. Unsupervised Feature Learning for Environmental Sound Classification Using Weighted Cycle Consistent Generative Adversarial Network. Applied Soft Computing. Accepted for Publications. October 2019. 

       
    29. S. Abdoli, P. Cardinal, A.L. Koerich. End-to-End Environmental Sound Classification using a Deep Convolutional Neural Network. Expert Systems with Applications, 136 (12) 252-263, 2019. 

       
    30. D. Vriesman, A.S. Britto Jr, A. Zimmer, R. Paludo, A.L. Koerich. Automatic Visual Inspection of Thermoelectric Metal Pipes. Signal, Image and Video Processing, 13 (5) 975-983, 2019. 

       
    Conferences

    1. Kwiatkowski, J., Lavertu, J. S., Gourrat, C., & Duchaine, V. Determining object properties from tactile events during grasp failure., In 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) (pp. 1692-1698). 

       
    2. Iturrate, I., Roberge, E., Østergaard, E. H., Duchaine, V., & Savarimuthu, T. R. Improving the generalizability of robot assembly tasks learned from demonstration via cnn-based segmentation., In 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) (pp. 553-560). 

       
    3. de Matos, J., de Souza Britto, A., de Oliveira, L. E. S., & Koerich, A. L. Texture CNN for Histopathological Image Classification, In 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) (pp. 580-583). 

       
    4. Luo, Jie, Sedghi Alireza , Popuri Karteek , Cobzas Dana, Zhang Miaomiao , Preiswerk Frank , Toews Matthew , Golby Alexandra , Sugiyama Masashi , Wells William M. , Frisken Sarah On the Applicability of Registration Uncertainty, International Conference on Medical Image Computing and Computer-Assisted Intervention MICCAI 2019 pp 410-419 

       
    5. Nicolas Tremblay, Kaveh Kamali, Philippe Cardou, Christian Desrosiers, Marc Gouttefarde, Martin J.-D. Otis Eye-on-Hand Calibration Method for Cable-Driven Parallel Robots, International Conference on Cable-Driven Parallel Robots. CableCon 2019: Cable-Driven Parallel Robots pp 345-356 

       
    6. Belghait, Fodil and April, Alain and Hamet, Pavel and Tremblay, Johanne and Desrosiers, Christian A large-scale and extensible platform for precision medicine research, Proceedings of the 9th International Conference on Digital Public Health (p. 47- 54), 2019 

       
    7. Chaddad, Ahmad and Daniel, Paul and Sabri, Siham and Desrosiers, Christian and Abdulkarim, Bassam Integration of radiomic and multi-omic analyses predicts survival of newly diagnosed IDH1 wild-type glioblastoma, Cancers, 2019, vol. 11, no 8, p. 1148 

       
    8. Soufiane Belharbi, Jérôme Rony, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, & Eric Granger Min-max Entropy for Weakly Supervised Pointwise Localization, Published as a conference paper at ICLR 2020 

       
    9. Francis Charette-Migneault, Eric Granger and Fania Mokhayeri Using Adaptive Trackers for Video Face Recognition froma Single Still Per Person, IPTA 2018: International Conference on Image Processing Theory, Tools and Applications 

       
    10. Madhu Kiran, Vivek Tiwari, Le Thanh Nguyen-Meidine, Louis-Antoine Blais Morin, Eric Granger On the Interaction Between Deep Detectors and Siamese Trackersin Video Surveillance, 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Nov 2019 

       
    11. Frank M. Hafner, Amran Bhuiyan, Julian F. P. Kooij, Eric Granger RGB-Depth Cross-Modal Person Re-identification, 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Nov 2019 

       
    12. Laurent Chauvin, Kuldeep Kumar, Christian Desrosiers,Jacques De Guise, William Wells III, and Matthew Toews Analyzing Brain Morphology on the Bag-of-Features Manifold, Information Processing in Medical Imaging June 2019 

       
    13. Souza, M.A., Cavalcanti, G.D.C., Cruz, R.M.O. and Sabourin, R., On Evaluating the Online Local Pool Generation Method for Imbalance Learning, 2019 International Joint Conference on Neural Networks (IJCNN-2019), Budapest, Hungary, July 14-19, 2019. 

       
    14. Souza, V.L.F., Oliveira, A.L.I., Cruz, R.M.O. and Sabourin, R., On Dissimilarity Representation and Transfer Learning for Offline Handwritten Signature Verification, 2019 International Joint Conference on Neural Networks (IJCNN-2019), Budapest, Hungary, July 14-19, 2019. 

       
    15. Souza, V.L.F., Oliveira, A.L.I., Cruz, R.M.O. and Sabourin, R., Characterization of Handwritten Signature Images in Dissimilarity Representation Space, International Conference on Computational Science (ICCS-2019), Faro, Algarve, Portugal, June 12-14, 2019. 

       
    16. Rony, J., Hafemann, L.G., Oliveira, L.S., Ben Ayed, I., Sabourin, R. and Granger, E., Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses, Conference on Computer Vision and Pattern Recognition (CVPR-2019), Long-Beach, CA, USA, June 15-21, 2019. 

       
    17. WC Melo, E Granger, A Hadid, Depression Detection based on Deep Distribution Learning, ICIP 2019: IEEE Int'l Conf. on Image Processing, Taipei, Taiwan, 2019. 

       
    18. X. Wu, T. H. Kinnunen, E. Granger, X. Feng, A. Hadid, Audio-Visual Kinship Verification in the Wild, ICB 2019: IAPR International Conference on Biometrics, Crete, Greece, 2019. 

       
    19. F. Mokhayeri, E. Granger, Robust Video Face Recognition From a Single Still Using a Synthetic Plus Variational Model, FG 2019: IEEE Int'l Conf. on Automatic Face and Gesture Recognition, Lille, France, 2019. 

       
    20. W. C. Melo, E. Granger, A. Hadid, Combining Global and Local Convolutional 3D Networks for Detecting Depression from Facial Expressions, FG 2019: IEEE Int'l Conf. on Automatic Face and Gesture Recognition, Lille, France, 2019. 

       
    21. H Kervadec, J Bouchtiba, C Desrosiers, E Granger, J Dolz, I Ben Ayed, Boundary loss for highly unbalanced segmentation, MIDL 2019: Int'l Conf. on Medical Imaging with Deep Learning, London, UK, 2019. 

       
    22. Zyblewski, P., Sabourin, R. and Wozniac, M., Data preprocessing and dynamic ensemble selection for imbalanced data stream classification, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2019), Würzburg, Germany, September 16-20, 2019. 

       
    23. Albuquerque, R., Costa, A., Santos, E.M., Sabourin, R. and Giusti, R., A Decision-Based Dynamic Ensemble Selection Method for Concept Drift, The IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Portland, Oregon, November 4-6, 2019. 

       
    24. D. Vriesman, A.S. Britto Jr, A. Zimmer, A.L. Koerich. Texture CNN for Thermoelectric Metal Pipe Image Classification. IEEE Intl Conf on Tools with Artificial Intelligence, Portland, USA, pp. 569-574, November 2019. 

       
    25. D.L. Tannugi, A.S. Britto Jr., A.L. Koerich. Memory Integrity of CNNs for Cross-Dataset Facial Expression Recognition. IEEE Intl Conf on Systems, Man, and Cybernetics, Bari, Italy, pp. 3806-3811, October 2019. 

       
    26. J.D.S. Ortega, P. Cardinal, A.L. Koerich. Emotion Recognition Using Fusion of Audio and Video Features. IEEE Intl Conf on Systems, Man, and Cybernetics, Bari, Italy, pp.3827-3832, October 2019. 

       
    27. J. Matos, A.S. Britto Jr., L.E.S. Oliveira, A.L. Koerich. Double Transfer Learning for Breast Cancer Histopathologic Image Classification. IEEE Intl Joint Conf on Neural Networks (IJCNN), Budapest, Hungary, pp.1-6, July 2019. 

       
    28. K.L. Wiggers, A.S. Britto Jr., L. Heutte, A.L. Koerich, L.E.S. Oliveira. Image Retrieval and Pattern Spotting using Siamese Neural Network. IEEE Intl Joint Conf on Neural Networks (IJCNN), Budapest, Hungary, pp.1-6, July 2019. 

       
    29. J. Matos, A.S. Britto Jr., L.E.S. Oliveira, A.L. Koerich. Texture CNN for Histopathologic Image Classification. 32nd IEEE Intl Symposium on Computer-Based Medical Systems (CBMS), Córdoba, Spain, pp.1-4, June 2019. 

       




    Année 2018:

    Revues

    1. Araújo, V. M., Britto, A. S., Brun, A. L., Koerich, A. L., & Oliveira, L. E. Fine-grained hierarchical classification of plant leaf images using fusion of deep models., In 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 1-5).  

       
    2. Jose Dolz, Xiaopan Xu, Jerome Rony, Jing Yuan, Yang Liu, Eric Granger, Christian Desrosiers, Xi Zhang, Ismail Ben Ayed, Hongbing Lu Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks, Medical Physics November 2018, pp 5482–5493  

       
    3. Jose Dolz, Xiaopan Xu, Jerome Rony, Jing Yuan, Yang Liu, Eric Granger, Christian Desrosiers, Xi Zhang, Ismail Ben Ayed, Hongbing Lu Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks, Medical Physics November 2018, pp 5482–5493  

       
    4. Jose Dolz, Xiaopan Xu, Jerome Rony, Jing Yuan, Yang Liu, Eric Granger, Christian Desrosiers, Xi Zhang, Ismail Ben Ayed, Hongbing Lu Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks, Medical Physics November 2018, pp 5482–5493  

       
    5. Inês Machado, Matthew Toews, Jie Luo, Prashin Unadkat, Walid Essayed, Elizabeth George, Pedro Teodoro, Herculano Carvalho, Jorge Martins, Polina Golland, Steve Pieper ,Sarah Frisken, Alexandra Golby, William WellsIII Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching, International Journal of Computer Assisted Radiology and Surgery October 2018, Volume 13, Issue 10, pp 1525–1538  

       
    6. Jie Luo, Sarah Frisken, Ines Machado, Miaomiao Zhang, Steve Pieper, Polina Golland, Matthew Toews, Prashin Unadkat, Alireza Sedghi, Haoyin Zhou, Alireza Mehrtash, Frank Preiswerk, Cheng-Chieh Cheng, Alexandra Golby, Masashi Sugiyama, William M. WellsIII Using the variogram for vector outlier screening: application to feature-based image registration, International Journal of Computer Assisted Radiology and Surgery December 2018, Volume 13, Issue 12, pp 1871–1880  

       
    7. R.M. Cruz, M.A. Souza, R. Sabourin and G.D. Cavalcanti On Dynamic Ensemble Selection and data Preprocessing for multi-class Imbalance Learning, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), November 2018. 

       
    8. Dolz, J. , Xu, X. , Rony, J. , Yuan, J. , Liu, Y. , Granger, E. , Desrosiers, C. , Zhang, X. , Ben Ayed, I. and Lu, H. , Multi‐region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks., Medical Physics, 2018. 

       
    9. Dolz J, Gopinath K, Yuan J, Lombaert H, Desrosiers C, Ben Ayed I., HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation., IEEE Transactions on Medical Imaging, 2018. 

       
    10. Mokhayeri, Fania, Granger, Eric, and Bilodeau Guillaume-Alexandre, Domain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per Person., IEEE Transactions on Information Forensics & Security, 2018. 

       
    11. Carbonneau, Marc-Andre, Granger, Eric, and Gagnon, Ghyslain, Bag-Level Aggregation for Multiple Instance Active Learning in Instance Classification Problems., IEEE Transactions on Neural Networks and Learning Systems, 2018. 

       
    12. MA Carbonneau, V Cheplygina, E Granger, G Gagnon, Multiple Instance Learning: A Survey of Problem Characteristics and Applications., Pattern Recognition 77, 329-353, 2018. 

       
    13. T Chakravorty, GA Bilodeau, E Granger, Tracking using Numerous Anchor Points., Machine Vision and Applications 29 (2), 247-261, 2018. 

       
    14. MA Carbonneau, E Granger, Y Attabi, G Gagnon, Feature Learning from Spectrograms for Assessment of Personality Traits., IEEE Transactions on Affective Computing, 2018. 

       
    15. Hafemann, L.G., Oliveira L.S. and Sabourin, R, Fixed-sized representation learning from Off-line Handwritten Signatures of different sizes, International Journal on Document Analysis and Recognition (IJDAR), Vol. 21, Issue 3, April 2018, pp 219-232. 

       
    16. Almeida, P.R.L., A.G., Oliveira L.S., Britto Jr, A. and Sabourin, R., Adapting Dynamic Classifier Selection for Concept Drift, Expert Systems with Applications, Vol. 104, August 2018, pp 67-85. 

       
    17. Roghayeh Soleymani, Eric Granger, Giorgio Fumera, Progressive Boosting for Class Imbalance and Its Application to Face Re-Identification, Expert Systems with Applications, July 2018. 

       
    18. Roy, A., Cruz, M.O.R., Sabourin, R. and Cavalcanti, G.D.C., A Study on Combining Dynamic Selection and Data Preprocessing for Imbalance Learning, Neurocomputing, January, 2018. 

       
    19. Cruz, M.O.R., Sabourin, R. and Cavalcanti, G.D.C., Prototype Selection for Dynamic Classifier and Ensemble Selection, Neural Computing and Applications, Vol 29, Issue 2, January 2018, pp 447-457. 

       
    20. Brun, A.L., Britto. A.S., Oliveira, L.E.S., Enembreck, F. and Sabourin, R., A Framework for Dynamic Classifier Selection Oriented by the Classification Problem Difficulty, Pattern Recognition, Vol. 76, April 2018, pp 175.190. 

       
    21. Cruz, M.O.R., Sabourin, R. and Cavalcanti, G.D.C., Dynamic Classifier Selection: Recent Advances and Perspectives, Information Fusion, Vol. 41, May 2018, pp 195-216. 

       
    22. Hochuli, A.G., Oliveira L.S., Britto Jr, A. and Sabourin, R., Handwritten Digit Segmentation: Is it still necessary?, Pattern Recognition, Vol. 78, June 2018, pp 1-11. 

       



    Conférences

    1. Kwiatkowski, J., Roberge, J. P., Nadeau, N. A., L'Écuyer-Lapierre, L., & Duchaine, V. An extrinsic dexterity approach to the IROS 2018 fan robotic challenge., In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4139-4144). 

       
    2. Wiggers, K. L., Britto, A. S., Heutte, L., Koerich, A. L., & Oliveira, L. E. S. Document image retrieval using deep features. In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8).  

       
    3. Kuldeep Kumar, Laurent Chauvin, Matthew Toews, Olivier Colliot, Christian Desrosiers Multi-Modal Analysis of Genetically-Related Subjects Using SIFT Descriptors in Brain MRI Computational Diffusion MRI pp 219-228  

       
    4. Jie Luo, Matthew Toews, Inês Machado, Sarah F. Frisken, Miaomiao Zhang, Frank Preiswerk, Alireza Sedghi, Hongyi Ding, Steven D. Pieper, Polina Golland, Alexandra J. Golby, Masashi Sugiyama, William M. Wells A Feature-Driven Active Framework for Ultrasound-Based Brain Shift Compensation International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 30-38) 

       
    5. Imtiaz Ziko, E Granger, I Ben Ayed, Scalable Laplacian K-modes., Neural Information Processing Systems (NIPS), Montreal, Canada, 2018. (spotlight) 

       
    6. Gupta A, Agrawal D, Chauhan H, Dolz J and Pedersoli M, An Attention Model for group-level emotion recognition., In Proceedings on ACM International Conference on Multimodal Interaction 2018 Oct 2 (pp. 611-615), 2018. 

       
    7. F Charette-Migneault, E Granger, F Mokhayeri, Using Adaptive Trackers for Video Face Recognition from a Single Still Per Person., International Conference on Image Processing Theory, Tools and and Applications (IPTA), Xi’an, China, 2018.  

       
    8. R Soleymani, E Granger, G Fumera, F-Measure Curves for Visualizing Classifier Performance with Imbalanced Data., IAPR Workshop on Artificial Neural Networks in Pattern Recognition (IANNPR) 2018.  

       
    9. I Amara, E Granger, A Hadid, Contextual Weighting of Patches for Local Matching in Still-to-Video Face Recognition., IEEE Conf. on Automatic Face and Gesture Recognition (FG), Workshop on Real-World Face and Object Recognition from Low-Quality Images, Xi'an, China, 2018.  

       
    10. Martins, J.G., Oliveira L.S., Sabourin, R. and Britto Jr, A.S., Forest species recognition based on ensemble of classifiers, 30th International Conference on Tools with Artificial Intelligence (ICTAI-2018), Volos, Greece, 5-7 November 2018. 

       
    11. Pereira, M.T., Britto Jr, A.S., Oliveira L.S. and Sabourin, R., Dynamic Ensemble Selection by K-Nearest Local Oracles with Discrimination Index, 30th International Conference on Tools with Artificial Intelligence (ICTAI-2018), Volos, Greece, 5-7 November 2018. 

       
    12. Silva, R.A., Britto Jr, A.S., Enembreck, F., Sabourin, R. and Oliveira L.S., Fusion of Classifiers based on Centrality Measures, 30th International Conference on Tools with Artificial Intelligence (ICTAI-2018), Volos, Greece, 5-7 November 2018. (Best Student Paper Award)

       
    13. Cao, H., Bernard, S., Heutte, L. and Sabourin, R, Dynamic voting in multi-view learning for radiomics applications, 1 IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition (SSPR'2018), Fragrance Hill, Beijing, China, August 17-19, 2018. 

       
    14. H. Kervadec, J.Dolz, M. Tang, E. Granger, Y. Boykov, I. B. Ayed, Size-constraint loss for weakly supervised CNN segmentation, Medical Imaging with Deep Learning (MIDL), Amsterdam, 4-6th July 2018. 

       
    15. Souza, V.L.S., Oliveira, A.L.I. and Sabourin, R., A Writer-independent Approach for Offline Signature Verification Using Deep Convolutional Neural Networks Features, The 7th Brazilian Conference on Intelligent Systems (BRACIS), Sao Paulo, Brazil, October 22-25, 2018. 

       
    16. Cao, H., Bernard, S., Heutte, L. and Sabourin, R., Improve the Performance of Transfer Learning without Fine-tuning using Dissimilarity-based Multi-view Learning for Breast Cancer Histology Images, 15th International Conference on Image Analysis and Recognition (ICIAR’2018), Póvoa de Varzim, Portugal, June 27-29, 2018. 

       
    17. Walmsley, F., Cavalcanti, G.D.C. Oliveira, D., Cruz, M.O.R., and Sabourin, R., An Ensemble Generation Method Based on Instance Hardness, International Joint Conference on Neural Networks (IJCNN), 8-13 July, 2018. 

       
    18. Hochuli, A.G., Oliveira L.S., Britto Jr, A. and Sabourin, R., Segmentation-Free Approaches for Handwritten Numeral String Recognition, International Joint Conference on Neural Networks (IJCNN), 8-13 July, 2018. 

       
    19. Oliveira, D.V.R., Cavalcanti, G.D.C., Porpino, T.N., Cruz, M.O.R., and Sabourin, R., K-Nearest Oracles Borderline Dynamic Classifier Ensemble Selection, International Joint Conference on Neural Networks (IJCNN), 8-13 July, 2018. 

       
    20. Ibtihel Amara, Eric Granger, Abdenour Hadid, Contextual Weighting of Patches for Local Matching in Still-to-Video Face Recognition, IEEE Conf. on Automatic Face and Gesture Recognition, Workshop on Real-World Face and Object Recognition from Low-Quality Images, Xi'an, China., 2018. 

       
    21. J.Dolz, J. Yuan, I. Ben Ayed, C. Desrosiers, Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network, In International Symposium on Biomedical Imaging (ISBI), 2018.  

       
    22. Cao, H., Bernard, S., Heutte, L. and Sabourin, R., Dissimilarity-based Representation for Radiomics Applications, First International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI'2018), Montreal, Canada, May 14-17, 2018. 

       
    23. Cruz, M.O.R., Sabourin, R. and Cavalcanti, G.D.C., On Dynamic Ensemble Selection and Data Preprocessing for Multi-class Imbalance Learning, First International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI'2018), Montreal, Canada, May 14-17, 2018. 

       


    Chapitres de livre


    1. S Bashbaghi, E Granger, R Sabourin, M Parchami, Deep Learning Architectures for Face Recognition in Video Surveillance, Deep Learning in Object Detection and Recognition, Springer, 2018. 

       



    Autres


    1. R. M. O. Cruz, L. G. Hafemann, R. Sabourin, and G. D. C. Cavalcanti, DESlib: A dynamic ensemble selection library in python, Journal of Machine Learning Research, vol. 21, No. 8, February 2020, pp. 1-5.  (github

       
    2. Dolz J, Gopinath K, Yuan J, Lombaert H, Desrosiers C, Ayed IB, HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation., arXiv preprint arXiv:1804.02967. 2018. 

       
    3. Jose Dolz, Xiaopan Xu, Jerome Rony, Jing Yuan, Yang Liu, Eric Granger, Christian Desrosiers, Xi Zhang, Ismail Ben Ayed, Hongbing Lu, Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks., arXiv preprint arXiv:1805.10720. May 2018. 

       
    4. Dolz J, Desrosiers C, Wang L, Yuan J, Shen D, Ayed IB, Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation., arXiv preprint arXiv:1712.05319. Dec 14, 2017 . 

       




    Année 2017:

    Revues

    1. Fechter T, Adebahr S, Baltas D, Ben Ayed I, Desrosiers C, Dolz J, Esophagus segmentation in CT via 3D fully convolutional neural network and random walk, Medical physics. 2017 Dec 1;44(12):6341-52. 

       
    2. Chakravorty, Tanushri and Bilodeau, Guillaume-Alexandre and Granger, Éric, Tracking using Numerous Anchor Points, Machine Vision and Applications, Springer, p. 1-15, issn = 0932-8092, December 2017. 

       
    3. Eskander, G.S., Sabourin R. and Granger E., Learning Global-Local Distance Metrics for Signature-Based Biometric Cryptosystems, Cryptography, Vol. 1, No 3, p. 23, November 2017. 

       
    4. Marc-Andre Carbonneau, Veronika Cheplygina, Eric Granger and Ghyslain Gagnon, Multiple instance learning: A survey of problem characteristics and applications, Pattern Recognition, October 2017. 

       
    5. Marc-Andre Carbonneau, Eric Granger, Yazid Attabi and Ghyslain Gagnon, Feature Learning from Spectrograms for Assessment of Personality Traits, IEEE Transactions on Affective Computing, 2017. 

       
    6. Idrissa Coulibaly, Nicolas Spiric, Richard Lepage and Michele St-Jacques, Semi-Automatic Road Extraction From VHR Images Based on Multiscale and Spectral Angle in Case of Earthquake, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017. 

       
    7. Hafemann, L.G., Oliveira L.S. and Sabourin, R., Learning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks, Pattern Recognition, vol.70, October 2017, pp 163-176. [Code and Pre-trained models]

       
    8. Oliveira, D.V.R., Cavalcanti, G.D.C. and Sabourin, R., Online Pruning of Base Classifiers for Dynamic Ensemble Selection, Pattern Recognition, vol. 72, December 2017, pp 44-58. 

       
    9. Dolz J, Desrosiers C, Ben Ayed I., 3D fully convolutional networks for subcortical segmentation: A large-scale study, Neuroimage, April 2017. (Accepted) 

       
    10. Bashbaghi, S., Granger, E., Sabourin, R. and Bilodeau, G-A, Dynamic Ensembles of Exemplar-SVMs for Still-to-Video Face Recognition, Pattern Recognition, vol. 69, September 2017, pp 61-81. 

       
    11. Gorelick L., Boykov Y., Veksler O., Ben Ayed I., and Delong A., Local sub-modularization for binary pairwise energies, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017. (Accepted)

       
    12. Mathlouthi, Y.; Mitiche, A. and Ben Ayed, I., Regularized differentiation for image derivatives, IET Image processing, 2017. (Accepted)

       
    13. Cruz, M.O.R., Sabourin, R. and Cavalcanti, G.D.C, META-DES.Oracle: Meta-learning and Feature Selection for Dynamic Ensemble Selection, Information Fusion, vol. 38, November 2017, pp 84-103. 

    14. Bashbaghi, S., Granger, E., Sabourin, R. and Bilodeau, G-A, Robust Watch-List Screening Using Ensembles Based on Multiple Face Representations, Machine Vision and Applications, vol. 28, No 1, January 2017, pp. 219-241. 

       


    Conférences

    1. Le Thanh Nguyen-Meidine, Eric Granger, Madhu Kiran and Louis-Antoine Blais-Morin, A Comparison of CNN-based Face and Head Detectors for Real-Time Video Surveillance Applications, The Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), Montreal, Canada, November 28 to December 1, 2017. 

       
    2. Cruz, M.O.R., Zakane, H.H., Sabourin, R. and Cavalcanti, G.D.C., Dynamic Ensemble Selection VS K-NN: why and when Dynamic Selection obtains Higher Classification Performance?, The Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), Montreal, Canada, November 28 to December 1, 2017.  

       
    3. Hafemann, L.G., Sabourin, R. and Oliveira L.S., Offline Handwritten Signature Verification - Literature Review, The Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), Montreal, Canada, November 28 to December 1, 2017.  

       
    4. Xihan Wang, Xiaoyi Feng, Zhaoqiang Xia, Jinye Peng, and Eric Granger, Multi-Orientation Scene Text Detection Leveraging Background Suppression, The 9th International Conference on Image and Graphics (ICIG), Shanghai, China, 13-15 September 2017. 

       
    5. Parchami M, Bashbaghi S, Granger E. and Sayed S, Using Deep Autoencoders to Learn Robust Domain-Invariant Representations for Still-to-Video Face Recognition, IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS), Leece, Italy, 29 Aug - 01 Sept 2017. 

       
    6. Parchami M, Bashbaghi S, Granger E, CNNs with Cross-Correlation Matching for Face Recognition in Video Surveillance Using a Single Training Sample Per Person, IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS), Leece, Italy, 29 Aug - 01 Sept 2017. 

       
    7. Dolz J, Ben Ayed I., Desrosiers C, Unbiased Shape Compactness for Segmentation, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Quebec City 2017. (Accepted and Awarded with the Student Travel MICCAI Award)

    8. Dolz J, Desrosiers C, Ben Ayed I., DOPE: Distributed Optimization for Pairwise Energies, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, Hawaii, 21-25 July 2017. 

       
    9. Bashbaghi, S., Granger, E., Sabourin, R. and Bilodeau, G-A,, Dynamic Selection of Exemplar-SVMs for Watch-List Screening Through Domain Adaptation, 6th International Conference on Pattern Recognition Applications and Methods (ICPRAM’2017), 24-26 February, Porto, Portugal, 2017. 

       
    10. Silva, E., Britto Jr., A.S., Oliveira, L.S., Enembreck, F., Sabourin, R., and Koerich, A., A Two-Step Cascade Classification Method, The International Joint Conference on Neural Networks (IJCNN'2017), Anchorage, Alaska, USA, 14-19 May 2017. 

       
    11. Mostafa Parchami, Saman Bashbaghi and Eric Granger, Video-Based Face Recognition Using Ensemble of Haar-Like Deep Convolutional Neural Networks, The International Joint Conference on Neural Networks (IJCNN'2017), Anchorage, Alaska, USA, 14-19 May 2017.. 

       
    12. Lévesque, J.C., Durand, A., Gagné, C. and Sabourin, R., Bayesian Optimization for Conditional Hyperparameter Spaces, The International Joint Conference on Neural Networks (IJCNN'2017), Anchorage, Alaska, USA, 14-19 May 2017.. 

       
    13. Souza, A.A., Cavalcanti, G.D.C., Cruz, M.O.R., and Sabourin, R., On the Characterization of the Oracle for Dynamic Classifier Selection, The International Joint Conference on Neural Networks (IJCNN'2017), Anchorage, Alaska, USA, 14-19 May 2017.. 

       
    14. Cruz, M.O.R., Sabourin, R. and Cavalcanti, G.D.C., Analyzing different prototype selection techniques for dynamic classifier and ensemble selection, The International Joint Conference on Neural Networks (IJCNN'2017), Anchorage, Alaska, USA, 14-19 May 2017..