Publications






Année 2018:

Revues

  1. 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), April 2018. (accepted). 

     
  2. 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. 

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

     
  4. 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. 

     
  5. 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. 

     
  6. 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. 

     
  7. 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. 

     
  8. 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. 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. 

     
  2. 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. 

     
  3. 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. 

     
  4. 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. 

     
  5. 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. 

     
  6. 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. 

     
  7. 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.  

     
  8. 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. 

     
  9. 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, arXiv:1802.04967, 2018.  (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..