ENGLISH |
Liste des publications de "Dolz, José"Nombre de documents archivés : 82. Article publié dans une revue, révisé par les pairs
Adiga V, Sukesh, Dolz, Jose et Lombaert, Herve.
2024.
« Anatomically-aware uncertainty for semi-supervised image segmentation ».
Medical Image Analysis, vol. 91.
Adiga V, Sukesh, Dolz, Jose et Lombaert, Herve.
2022.
« Attention-based dynamic subspace learners for medical image analysis ».
IEEE Journal of Biomedical and Health Informatics, vol. 26, nº 9.
pp. 4599-4610.
Bandyk, Mark G., Gopireddy, Dheeraj R., Lall, Chandana, Balaji, K. C. et Dolz, Jose.
2021.
« MRI and CT bladder segmentation from classical to deep learning based approaches: Current limitations and lessons ».
Computers in Biology and Medicine, vol. 134.
Bateson, M., Dolz, J., Kervadec, H., Lombaert, H. et Ben Ayed, I..
2021.
« Constrained domain adaptation for image segmentation ».
IEEE Transactions on Medical Imaging, vol. 40, nº 7.
pp. 1875-1887.
Bateson, Mathilde, Kervadec, Hoel, Dolz, Jose, Lombaert, Hervé et Ben Ayed, Ismail.
2022.
« Source-free domain adaptation for image segmentation ».
Medical Image Analysis, vol. 82.
Beizaee, Farzad, Bona, Michele, Desrosiers, Christian, Dolz, Jose et Lodygensky, Gregory.
2023.
« Determining regional brain growth in premature and mature infants in relation to age at MRI using deep neural networks ».
Scientific Reports, vol. 13, nº 1.
Belharbi, Soufiane, Rony, Jérôme, Dolz, Jose, Ben Ayed, Ismail, McCaffrey, Luke et Granger, Eric.
2022.
« Deep interpretable classification and weakly-supervised segmentation of histology images via max-min uncertainty ».
IEEE Transactions on Medical Imaging, vol. 41, nº 3.
pp. 702-714.
Carass, Aaron, Cuzzocreo, Jennifer L., Han, Shuo, Hernandez-Castillo, Carlos R., Rasser, Paul E., Ganz, Melanie, Beliveau, Vincent, Dolz, Jose, Ben Ayed, Ismail, Desrosiers, Christian, Thyreau, Benjamin, Romero, José E., Coupé, Pierrick, Manjón, José V., Fonov, Vladimir S., Collins, D. Louis, Ying, Sarah H., Onyike, Chiadi U., Crocetti, Deana, Landman, Bennett A., Mostofsky, Stewart H., Thompson, Paul M. et Prince, Jerry L..
2018.
« Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images ».
NeuroImage, vol. 183.
pp. 150-172.
Ding, Yang, Acosta, Ronaldo, Enguix, Vicente, Suffren, Sabrina, Ortmann, Janosch, Luck, David, Dolz, Jose et Lodygensky, Gregory A..
2020.
« Using deep convolutional neural networks for neonatal brain image segmentation ».
Frontiers in Neuroscience, vol. 14.
Dolz, J., Kirisli, H. A., Fechter, T., Karnitzki, S., Oehlke, O., Nestle, U., Vermandel, M. et Massoptier, L..
2016.
« Interactive contour delineation of organs at risk in radiotherapy: clinical evaluation on NSCLC patients ».
Medical Physics, vol. 43, nº 5.
pp. 2569-2580.
Dolz, Jose, Betrouni, Nacim, Quidet, Mathilde, Kharroubi, Dris, Leroy, Henri A., Reyns, Nicolas, Massoptier, Laurent et Vermandel, Maximilien.
2016.
« Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study ».
Computerized Medical Imaging and Graphics, vol. 52.
pp. 8-18.
Dolz, Jose, Desrosiers, Christian et Ben Ayed, Ismail.
2018.
« 3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study ».
NeuroImage, vol. 170.
pp. 456-470.
Dolz, Jose, Desrosiers, Christian, Wang, Li, Yuan, Jing, Shen, Dinggang et Ben Ayed, Ismail.
2020.
« Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation ».
Computerized Medical Imaging and Graphics, vol. 79.
Dolz, Jose, Gopinath, Karthik, Yuan, Jing, Lombaert, Herve, Desrosiers, Christian et Ben Ayed, Ismail.
2019.
« HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation ».
IEEE Transactions on Medical Imaging, vol. 38, nº 5.
pp. 1116-1126.
Dolz, Jose, Xu, Xiaopan, Rony, Jérôme, Yuan, Jing, Liu, Yang, Granger, Éric, Desrosiers, Christian, Zhang, Xi, Ben Ayed, Ismail et Lu, Hongbing.
2018.
« Multiregion segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks ».
Medical Physics, vol. 45, nº 12.
pp. 5482-5493.
Fechter, Tobias, Adebahr, Sonja, Baltas, Dimos, Ben Ayed, Ismail, Desrosiers, Christian et Dolz, Jose.
2017.
« Esophagus segmentation in CT via 3D fully convolutional neural network and random walk ».
Medical Physics, vol. 44, nº 12.
pp. 6341-6352.
Galdran, A., Chakor, H., Kabir, W., Kobbi, R., Liu, B., Dolz, J. et Ben Ayed, I..
2022.
« An automatic deep learning-based system for screening and management of DME ».
[Résumé d'une communication à une conférence]. Diabetes Research and Clinical Practice, vol. 186, nº Suppl. 1.
pp. 4-5.
Galdran, Adrian, Anjos, André, Dolz, José, Chakor, Hadi, Lombaert, Hervé et Ben Ayed, Ismail.
2022.
« State-of-the-art retinal vessel segmentation with minimalistic models ».
Scientific Reports, vol. 12, nº 1.
Galdran, Adrian, Chelbi, Jihed, Kobi, Riadh, Dolz, José, Lombaert, Hervé, Ben Ayed, Ismail et Chakor, Hadi.
2020.
« Non-uniform label smoothing for diabetic retinopathy grading from retinal fundus images with deep neural networks ».
Translational Vision Science and Technology, vol. 9, nº 2.
Gumus, Kazim Z., Nicolas, Julien, Gopireddy, Dheeraj R., Dolz, Jose, Jazayeri, Seyed Behzad et Bandyk, Mark.
2024.
« Deep learning algorithms for bladder cancer segmentation on multi-parametric MRI ».
Cancers, vol. 16, nº 13.
Kervadec, Hoel, Bouchtiba, Jihene, Desrosiers, Christian, Granger, Eric, Dolz, José et Ben Ayed, Ismail.
2021.
« Boundary loss for highly unbalanced segmentation ».
Medical Image Analysis, vol. 67.
Kervadec, Hoel, Dolz, Jose, Tang, Meng, Granger, Éric, Boykov, Yuri et Ben Ayed, Ismail.
2019.
« Constrained-CNN losses for weakly supervised segmentation ».
Medical Image Analysis, vol. 54.
pp. 88-99.
Kim, Bach Ngoc, Dolz, Jose, Jodoin, Pierre-Marc et Desrosiers, Christian.
2021.
« Privacy-net: An adversarial approach for identity-obfuscated segmentation of medical images ».
IEEE Transactions on Medical Imaging, vol. 40, nº 7.
pp. 1737-1749.
Liu, Bingyuan, Desrosiers, Christian, Ben Ayed, Ismail et Dolz, Jose.
2023.
« Segmentation with mixed supervision: Confidence maximization helps knowledge distillation ».
Medical Image Analysis, vol. 83.
Liu, Bingyuan, Dolz, Jose, Galdran, Adrian, Kobbi, Riadh et Ben Ayed, Ismail.
2024.
« Do we really need dice? The hidden region-size biases of segmentation losses ».
Medical Image Analysis, vol. 91.
Murugesan, Balamurali, Liu, Bingyuan, Galdran, Adrian, Ayed, Ismail Ben et Dolz, Jose.
2023.
« Calibrating segmentation networks with margin-based label smoothing ».
Medical Image Analysis, vol. 87.
Nguyen-Meidine, Le Thanh, Belal, Atif, Kiran, Madhu, Dolz, Jose, Blais-Morin, Louis-Antoine et Granger, Eric.
2021.
« Knowledge distillation methods for efficient unsupervised adaptation across multiple domains ».
Image and Vision Computing, vol. 108.
Nguyen-Meidine, Le Thanh, Kiran, Madhu, Pedersoli, Marco, Dolz, Jose, Blais-Morin, Louis-Antoine et Granger, Eric.
2022.
« Incremental multi-target domain adaptation for object detection with efficient domain transfer ».
Pattern Recognition, vol. 129.
Patel, Gaurav et Dolz, Jose.
2022.
« Weakly supervised segmentation with cross-modality equivariant constraints ».
Medical Image Analysis, vol. 77.
Peng, Jizong, Kervadec, Hoel, Dolz, Jose, Ben Ayed, Ismail, Pedersoli, Marco et Desrosiers, Christian.
2020.
« Discretely-constrained deep network for weakly supervised segmentation ».
Neural Networks, vol. 130.
pp. 297-308.
Silva-Rodríguez, Julio, Chakor, Hadi, Kobbi, Riadh, Dolz, Jose et Ben Ayed, Ismail.
2025.
« A Foundation Language-Image Model of the Retina (FLAIR): Encoding expert knowledge in text supervision ».
Medical Image Analysis, vol. 99.
Silva-Rodriguez, Julio, Colomer, Adrián, Dolz, Jose et Naranjo, Valery.
2021.
« Self-learning for weakly supervised gleason grading of local patterns ».
IEEE Journal of Biomedical and Health Informatics, vol. 25, nº 8.
pp. 3094-3104.
Silva-Rodríguez, Julio, Naranjo, Valery et Dolz, Jose.
2022.
« Constrained unsupervised anomaly segmentation ».
Medical Image Analysis, vol. 80.
Sinha, Ashish et Dolz, José.
2021.
« Multi-scale self-guided attention for medical image segmentation ».
IEEE Journal of Biomedical and Health Informatics, vol. 25, nº 1.
pp. 121-130.
Wang, Li, Nie, Dong, Guannan, Li, Puybareau, Élodie, Dolz, Jose, Zhang, Qian, Wang, Fan, Xia, Jing, Wu, Zhengwang, Chen, Jia-Wei, Thung, Kim-Han, Bui, Toan Duc, Shin, Jitae, Zeng, Guodong, Zheng, Guoyan, Fonov, Vladimir S., Doyle, Andrew, Xu, Yongchao, Moeskops, Pim, Pluim, Josien P. W., Desrosiers, Christian, Ben Ayed, Ismail, Sanroma, Gerard, Benkarim, Oualid M., Casamitjana, Adrià, Vilaplana, Verónica, Lin, Weili, Li, Gang et Shen, Dinggang.
2019.
« Benchmark on automatic six-month-old infant brain segmentation algorithms: the iSeg-2017 challenge ».
IEEE Transactions on Medical Imaging, vol. 38, nº 9.
pp. 2219-2230.
Xu, Xiaopan, Zhang, Xi, Tian, Qian, Wang, Huanjun, Cui, Long-Biao, Li, Shurong, Tang, Xing, Li, Baojun, Dolz, Jose, Ben Ayed, Ismail, Liang, Zhengrong, Yuan, Jing, Du, Peng, Lu, Hongbing et Liu, Yang.
2019.
« Quantitative identification of nonmuscle-invasive and muscle-invasive bladder carcinomas: a multiparametric MRI radiomics analysis ».
Journal of Magnetic Resonance Imaging, vol. 49, nº 5.
pp. 1489-1498. Compte rendu de conférence
Adiga Vasudeva, Sukesh, Dolz, Jose et Lombaert, Herve.
2023.
« GeoLS: Geodesic label smoothing for image segmentation ».
In International Confefence on Medical Imaging with Deep Learning (MIDL) (Nashville, TN, USA, July 10-12, 2023)
Coll. « Proceedings of Machine Learning Research », vol. 227.
pp. 468-478.
ML Research Press.
Adiga Vasudeva, Sukesh, Dolz, Jose et Lombaert, Herve.
2022.
« Leveraging labeling representations in uncertainty-based semi-supervised segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 25th International Conference ; Proceedings, Part VIII (Singapore, Singapore, Sept. 18-22, 2022)
Coll. « Lecture Notes in Computer Science », vol. 13438.
pp. 265-275.
Springer Science and Business Media Deutschland GmbH.
Azad, Reza, Fayjie, Abdur R., Kauffmann, Claude, Ben Ayed, Ismail, Pedersoli, Marco et Dolz, Jose.
2021.
« On the texture bias for few-shot CNN segmentation ».
In IEEE Winter Conference on Applications of Computer Vision (WACV) (En ligne, Jan. 05-09, 2021)
pp. 2673-2682.
Institute of Electrical and Electronics Engineers.
Bateson, Mathilde, Kervadec, Hoel, Dolz, Jose, Lombaert, Hervé et Ben Ayed, Ismail.
2019.
« Constrained domain adaptation for segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Proceedings, Part II (Shenzhen, China, Oct. 13-17, 2019)
Coll. « Lecture Notes in Computer Science », vol. 11765.
pp. 326-334.
Springer.
Bateson, Mathilde, Kervadec, Hoel, Dolz, José, Lombaert, Hervé et Ben Ayed, Ismail.
2020.
« Source-relaxed domain adaptation for image segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 : 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part I (Lima, Peru, Oct. 04-08, 2020)
Coll. « Lecture Notes in Computer Science », vol. 12261.
pp. 490-499.
Springer Science and Business Media Deutschland GmbH.
Beizaee, Farzad, Desrosiers, Christian, Lodygensky, Gregory A. et Dolz, Jose.
2023.
« Harmonizing flows: Unsupervised MR harmonization based on normalizing flows ».
In Information Processing in Medical Imaging : 28th International Conference, IPMI : Proceedings (San Carlos de Bariloche, Argentina, June 18-23, 2023)
Coll. « Lecture Notes in Computer Science », vol. 13939.
pp. 347-359.
Springer.
Boudiaf, Malik, Kervadec, Hoel, Masud, Ziko Imtiaz, Piantanida, Pablo, Ben Ayed, Ismail et Dolz, Jose.
2021.
« Few-shot segmentation without meta-learning: A good transductive inference is all you need? ».
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (Nashville, TN, USA, June 20-25, 2021)
pp. 13974-13983.
IEEE.
Boudiaf, Malik, Masud, Ziko Imtiaz, Rony, Jérôme, Dolz, Jose, Piantanida, Pablo et Ben Ayed, Ismail.
2020.
« Transductive information maximization for few-shot learning ».
In Neural Information Processing Systems Online Conference (NeuroIPS) (En ligne, Dec. 06-12, 2020)
Chiaroni, Florent, Dolz, Jose, Masud, Ziko Imtiaz, Mitiche, Amar et Ben Ayed, Ismail.
2023.
« Parametric information maximization for generalized category discovery ».
In IEEE/CVF International Conference on Computer Vision (ICCV) (Paris, France, Oct. 01-06, 2023)
pp. 1729-1739.
Institute of Electrical and Electronics Engineers Inc..
Dolz, J., Leroy, H. A., Reyns, N., Massoptier, L. et Vermandel, M..
2015.
« A fast and fully automated approach to segment optic nerves on MRI and its application to radiosurgery ».
In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) (New York, NY, USA, April 16-19, 2015)
pp. 1102-1105.
Piscataway, NJ, USA : IEEE.
Dolz, Jose, Ben Ayed, Ismail et Desrosiers, Christian.
2017.
« DOPE: distributed optimization for pairwise energies ».
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Honolulu, HI, USA, July 21-26, 2017)
pp. 4095-4104.
IEEE Computer Society.
Dolz, Jose, Ben Ayed, Ismail et Desrosiers, Christian.
2019.
« Dense multi-path U-Net for ischemic stroke lesion segmentation in multiple image modalities ».
In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries : 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers, Part I (Granada, Spain, Sept. 16-20, 2018)
Coll. « Lecture Notes in Computer Science », vol. 11383.
pp. 271-282.
Cham, Switzerland : Springer.
Dolz, Jose, Ben Ayed, Ismail et Desrosiers, Christian.
2017.
« Unbiased shape compactness for segmentation ».
In Medical Image Computing and Computer-Assisted Intervention : MICCAI 2017 : 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017 : Proceedings : Part I (Quebec City, QC, Canada, Sept. 11-13, 2017)
Coll. « Lecture Notes in Computer Science », vol. 10433.
pp. 755-763.
Springer Verlag.
Dolz, Jose, Ben Ayed, Ismail, Jing, Yuan et Desrosiers, Christian.
2018.
« Isointense infant brain segmentation with a hyper-dense connected convolutional neural network ».
In IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) (Washington, DC, USA, Apr. 04-07, 2018)
pp. 616-620.
Piscataway, NJ, USA : IEEE.
Dolz, Jose, Desrosiers, Christian et Ben Ayed, Ismail.
2019.
« IVD-Net: intervertebral disc localization and segmentation in MRI with a multi-modal UNet ».
In Computational Methods and Clinical Applications for Spine Imaging : 5th International Workshop and Challenge, CSI 2018, Held in Conjonction with MICCAI 2018. Revised Selected Papers (Granada, Spain, Sept. 16, 2018)
Coll. « Lecture Notes in Computer Science », vol. 11397.
pp. 130-143.
Springer Verlag.
Dolz, Jose, Desrosiers, Christian et Ben Ayed, Ismail.
2021.
« Teach me to segment with mixed supervision: Confident students become masters ».
In 27th International Conference on Information Processing in Medical Imaging, IPMI 2021, Virtual, Online, 28 June 2021 - 30 June 2021 (En ligne, June 28-30, 2021)
Coll. « Lecture Notes in Computer Science », vol. 12729.
pp. 517-529.
Springer.
Galdran, Adrian, Dolz, Jose, Chakor, Hadi, Lombaert, Hervé et Ben Ayed, Ismail.
2020.
« Cost-sensitive regularization for diabetic retinopathy grading from eye fundus images ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part V (Lima, Peru, Oct. 04-08, 2020)
Coll. « Lecture Notes in Computer Science », vol. 12265.
pp. 665-674.
Springer International Publishing.
Garcia, Gabriel, Colomer, Adrian, Verdu-Monedero, Rafael, Dolz, Jose et Naranjo, Valery.
2021.
« A self-training framework for glaucoma grading in OCT B-scans ».
In 29th European Signal Processing Conference (EUSIPCO) (Dublin, Ireland, Aug. 23-27, 2021)
pp. 1281-1285.
IEEE.
Gupta, Aarush, Agrawal, Dakshit, Chauhan, Hardik, Dolz, Jose et Pedersoli, Marco.
2018.
« An attention model for group-level emotion recognition ».
In 20th ACM International Conference on Multimodal Interaction (ICIM '18) (Boulder, CO, USA, Oct. 16-20, 2018)
pp. 611-615.
ACM.
Hajimiri, Sina, Boudiaf, Malik, Ben Ayed, Ismail et Dolz, Jose.
2023.
« A strong baseline for generalized few-shot semantic segmentation ».
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (Vancouver, BC, Canada, June 17-24, 2023)
pp. 11269-11278.
IEEE.
Kervadec, H., Dolz, J., Yuan, J., Desrosiers, C., Granger, E. et Ben Ayed, I..
2022.
« Constrained deep networks: Lagrangian optimization via Log-barrier extensions ».
In 30th European Signal Processing Conference (EUSIPCO) (Belgrade, Serbia, Aug. 29-Sept. 02, 2022)
pp. 962-966.
European Signal Processing Conference, EUSIPCO.
Kervadec, Hoel, Bahig, Houda, Letourneau-Guillon, Laurent, Dolz, Jose et Ben Ayed, Ismail.
2021.
« Beyond pixel-wise supervision: semantic segmentation with higher-order shape descriptors ».
In Proceedings of the Fourth Conference on Medical Imaging with Deep Learning (Lübeck, Germany, En ligne, July 07-09, 2021)
Coll. « Proceedings of Machine Learning Research », vol. 143.
pp. 354-368.
PMLR.
Kervadec, Hoel, Bouchtiba, Jihene, Desrosiers, Christian, Granger, Eric, Dolz, Jose et Ben Ayed, Ismail.
2019.
« Boundary loss for highly unbalanced segmentation ».
In 2nd International Conference on Medical Imaging with Deep Learning (MIDL) (London, England, July 08-10, 2019)
Coll. « Proceedings of Machine Learning Research », vol. 102.
pp. 285-296.
PMLR.
Kervadec, Hoel, Dolz, Jose, Granger, Éric et Ben Ayed, Ismail.
2019.
« Curriculum semi-supervised segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Proceedings, Part II (Shenzhen, China, Oct 13-17, 2019)
Coll. « Lecture Notes in Computer Science », vol. 11765.
pp. 568-576.
Springer.
Kervadec, Hoel, Dolz, Jose, Tang, Meng, Granger, Éric, Boykov, Yuri et Ben Ayed, Ismail.
2018.
« Constrained-CNN losses for weakly supervised segmentation ».
In 1st Conference on Medical Imaging with Deep Learning (MIDL 2018) (Amsterdam, Netherlands, July 4-6, 2018)
Kervadec, Hoel, Dolz, Jose, Wang, Shanshan, Granger, Eric et Ben Ayed, Ismail.
2020.
« Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision ».
In Medical Imaging with Deep Learning, 6-8 July 2020, Montreal, QC, Canada (Montreal, QC, Canada, July 06-08, 2020)
Coll. « Proceedings of Machine Learning Research », vol. 121.
pp. 365-381.
PLMR.
Kim, Bach Ngoc, Dolz, Jose, Desrosiers, Christian et Jodoin, Pierre-Marc.
2021.
« Privacy preserving for medical image analysis via non-linear deformation proxy ».
In 32nd British Machine Vision Conference, BMVC (Online, Nov. 22-25, 2021)
British Machine Vision Association, BMVA.
Kim, Bach Ngoc, Dolz, Jose, Jodoin, Pierre-Marc et Desrosiers, Christian.
2023.
« Mixup-privacy: A simple yet effective approach for privacy-preserving segmentation ».
In Information Processing in Medical Imaging : 28th International Conference, IPMI : Proceedings (San Carlos de Bariloche, Argentina, June 18-23, 2023)
Coll. « Lecture Notes in Computer Science », vol. 13939.
pp. 717-729.
Springer.
Larrazabal, Agostina J., Martínez, César, Dolz, José et Ferrante, Enzo.
2023.
« Maximum entropy on erroneous predictions: Improving model calibration for medical image segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 : 26th International Conference, Proceedings (Vancouver, BC, Canada, Oct. 08-12, 2023)
Coll. « Lecture Notes in Computer Science », vol. 14222.
pp. 273-283.
Springer Science and Business Media Deutschland GmbH.
Larrazabal, Agostina J., Martínez, César, Dolz, Jose et Ferrante, Enzo.
2021.
« Orthogonal ensemble networks for biomedical image segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part III (Strasbourg, France, Sept. 27-Oct. 01, 2021)
Coll. « Lecture Notes in Computer Science », vol. 12903.
pp. 594-603.
Springer Science and Business Media.
Le Thanh, Nguyen-Meidine, Granger, Eric, Kiran, Madhu, Dolz, Jose et Blais-Morin, Louis-Antoine.
2020.
« Joint progressive knowledge distillation and unsupervised domain adaptation ».
In International Joint Conference on Neural Networks (IJCNN) (Glasgow, United Kingdom, July 19-24, 2020)
Piscataway, NJ, USA : IEEE.
Liu, Bingyuan, Ben Ayed, Ismail, Galdran, Adrian et Dolz, Jose.
2022.
« The devil is in the margin: Margin-based label smoothing for network calibration ».
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (New Orleans, LA, USA, June 18-24, 2022)
pp. 80-88.
Liu, Bingyuan, Rony, Jérôme, Galdran, Adrian, Dolz, Jose et Ben Ayed, Ismail.
2023.
« Class adaptive network calibration ».
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (Vancouver, BC, Canada, June 17-24, 2023)
pp. 16070-16079.
IEEE Computer Society.
Murugesan, Balamurali, Adiga Vasudeva, Sukesh, Liu, Bingyuan, Lombaert, Herve, Ben Ayed, Ismail et Dolz, Jose.
2023.
« Trust your neighbours: Penalty-based constraints for model calibration ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 : 26th International Conference, Proceedings (Vancouver, BC, Canada, Oct. 08-12, 2023)
Coll. « Lecture Notes in Computer Science », vol. 14222.
pp. 572-581.
Springer Science and Business Media Deutschland GmbH.
Murugesan, Balamurali, Hussain, Rukhshanda, Bhattacharya, Rajarshi, Ben Ayed, Ismail et Dolz, Jose.
2024.
« Prompting classes: Exploring the power of prompt class learning in weakly supervised semantic segmentation ».
In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (Waikoloa, HI, USA, Jan. 03-08, 2024)
pp. 290-301.
Institute of Electrical and Electronics Engineers Inc..
Murugesan, Balamurali, Silva-Rodriguez, Julio, Ben Ayed, Ismail et Dolz, Jose.
2024.
« Class and region-adaptive constraints for network calibration ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Proceedings, Part VIII (Marrakesh, Morocco, Oct. 06-10, 2024)
Coll. « Lecture Notes in Computer Science », vol. 15008.
pp. 57-67.
Springer.
Murugesan, Balamurali, Silva-Rodríguez, Julio, ben Ayed, Ismail et Dolz, Jose.
2025.
« Robust calibration of large vision-language adapters ».
In Computer Vision – ECCV 2024 : 18th European Conference, 2024, Proceedings, Part XXI (Milan, Italy, Sept. 29-Oct. 04, 2024)
Coll. « Lecture notes in computer science », vol. 15082.
pp. 147-165.
Springer.
Nguyen-Meidine, L. T., Belal, A., Kiran, M., Dolz, J., Blais-Morin, L. A. et Granger, E..
2021.
« Unsupervised multi-target domain adaptation through knowledge distillation ».
In IEEE Winter Conference on Applications of Computer Vision (WACV) (Waikoloa, HI, USA, Jan. 03-08, 2021)
pp. 1338-1346.
Los Alamitos, CA, USA : IEEE Computer Society.
Nicolas, Julien, Chiaroni, Florent, Ziko, Imtiaz, Ahmad, Ola, Desrosiers, Christian et Dolz, Jose.
2024.
« MoP-CLIP: A mixture of prompt-tuned CLIP models for domain incremental learning ».
In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (Waikoloa, HI, USA, Jan. 03-08, 2024)
pp. 1751-1761.
Institute of Electrical and Electronics Engineers Inc..
Pichler, Georg, Dolz, Jose, Ben Ayed, Ismail et Piantanida, Pablo.
2020.
« On direct distribution matching for adapting segmentation networks ».
In Medical Imaging with Deep Learning, 6-8 July 2020, Montreal, QC, Canada (Montreal, QC, Canada, July 06-08, 2020)
Coll. « Proceedings of Machine Learning Research », vol. 121.
pp. 624-637.
PLMR.
Shakeri, Fereshteh, Huang, Yunshi, Silva-Rodríguez, Julio, Bahig, Houda, Tang, An, Dolz, José et Ben Ayed, Ismail.
2024.
« Few-shot adaptation of medical vision-language models ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Proceedings, Part XII (Marrakesh, Morocco, Oct. 06-10, 2024)
Coll. « Lecture notes in computer science », vol. 15012.
pp. 553-563.
Springer.
Silva-Rodriguez, Julio, Chelbi, Jihed, Kabir, Waziha, Chakor, Hadi, Dolz, Jose, Ben Ayed, Ismail et Kobbi, Riadh.
2024.
« Exploring the transferability of a foundation model for fundus images: Application to hypertensive retinopathy ».
In Advances in Computer Graphics : 40th Computer Graphics International Conference, CGI : Proceedings (Shanghai, China, Aug. 28-Sept. 01, 2023)
Coll. « Lecture Notes in Computer Science », vol. 14497.
pp. 427-437.
Springer Science and Business Media Deutschland GmbH.
Silva-Rodríguez, Julio, Dolz, José et Ben Ayed, Ismail.
2023.
« Towards foundation models and few-shot parameter-efficient fine-tuning for volumetric organ segmentation ».
In Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops : ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023 : Proceedings (Vancouver, BC, Canada, Oct. 08-12, 2023)
Coll. « Lecture Notes in Computer Science », vol. 14393.
pp. 213-224.
Springer Science and Business Media.
Van Waerebeke, Martin, Lodygensky, Gregory et Dolz, Jose.
2022.
« On the pitfalls of entropy-based uncertainty for multi-class semi-supervised segmentation ».
In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging : 4th International Workshop, UNSURE 2022, Held in Conjunction with MICCAI 2022 : Proceedings (Singapore, Singapore, Sept. 18, 2022)
Coll. « Lecture Notes in Computer Science », vol. 13563.
pp. 36-46.
Springer Science and Business Media Deutschland GmbH.
Ziko, Imtiaz Masud, Dolz, Jose, Granger, Eric et Ben Ayed, Ismail.
2020.
« Laplacian regularized few-shot learning ».
In 37th International Conference on Machine Learning (ICML) (En ligne, July 12-18, 2020)
pp. 11596-11606.
CommunicationBen Ayed, Ismail, Desrosiers, Christian et Dolz, Jose. 2019. « Tutorial : Weakly supervised CNN segmentation: Models and optimization ». Communication lors de la conférence : Medical Image Computing and Computer Assisted Intervention (MICCAI) (Shenzen, China, Oct. 13-17, 2019). |