Publications 2018

Year 2018:
Journals  
 
  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. 

     
 


Conferences

  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. 

     


Book Chapters


  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. 

     


Others


  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 .