Behzad Bozorgtabar
Orcid: 0000-0002-5759-4896
According to our database1,
Behzad Bozorgtabar
authored at least 79 papers
between 2011 and 2024.
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Bibliography
2024
Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology.
IEEE Trans. Medical Imaging, May, 2024
Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime.
Comput. Biol. Medicine, February, 2024
ALFREDO: Active Learning with FeatuRe disEntangelement and DOmain adaptation for medical image classification.
Medical Image Anal., 2024
GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification.
Medical Image Anal., 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Combining Graph Transformers Based Multi-Label Active Learning and Informative Data Augmentation for Chest Xray Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Weakly supervised joint whole-slide segmentation and classification in prostate cancer.
Medical Image Anal., October, 2023
Source-Free Open-Set Domain Adaptation for Histopathological Images via Distilling Self-Supervised Vision Transformer.
CoRR, 2023
Self-Supervised Learning-Based Cervical Cytology Diagnostics in Low-Data Regime and Low-Resource Setting.
CoRR, 2023
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023
Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
AMAE: Adaptation of Pre-trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
SaGTTA: Saliency Guided Test Time Augmentation for Medical Image Segmentation Across Vendor Domain Shift.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Adaptive Similarity Bootstrapping for Self-Distillation based Representation Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Attention-Conditioned Augmentations for Self-Supervised Anomaly Detection and Localization.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection.
Medical Image Anal., 2022
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Unsupervised Domain Adaptation Using Feature Disentanglement and GCNs for Medical Image Classification.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022
Medical Image Super Resolution by Preserving Interpretable and Disentangled Features.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022
Anomaly Detection and Localization Using Attention-Guided Synthetic Anomaly and Test-Time Adaptation.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022
2021
IEEE Trans. Medical Imaging, 2021
Self-Rule to Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection.
CoRR, 2021
Benefiting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Self-Rule to Adapt: Learning Generalized Features from Sparsely-Labeled Data Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Phenotyping.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
Self-supervised Learning of Inter-label Geometric Relationships for Gleason Grade Segmentation.
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels Using Tissue Graphs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021
SOoD: Self-Supervised Out-of-Distribution Detection Under Domain Shift for Multi-Class Colorectal Cancer Tissue Types.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
Pattern Recognit., 2020
Neurocomputing, 2020
Benefitting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution.
CoRR, 2020
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation.
CoRR, 2020
Structure Preserving Stain Normalization of Histopathology Images Using Self Supervised Semantic Guidance.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2019
DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation.
EURASIP J. Image Video Process., 2019
Informative sample generation using class aware generative adversarial networks for classification of chest Xrays.
Comput. Vis. Image Underst., 2019
CoRR, 2019
Image super-resolution using progressive generative adversarial networks for medical image analysis.
Comput. Medical Imaging Graph., 2019
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis.
Proceedings of the 14th IEEE International Conference on Automatic Face & Gesture Recognition, 2019
G2-VER: Geometry Guided Model Ensemble for Video-based Facial Expression Recognition.
Proceedings of the 14th IEEE International Conference on Automatic Face & Gesture Recognition, 2019
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019
2018
IEEE Trans. Circuits Syst. Video Technol., 2018
CoRR, 2018
Efficient Active Learning for Image Classification and Segmentation Using a Sample Selection and Conditional Generative Adversarial Network.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
2017
Skin lesion segmentation using deep convolution networks guided by local unsupervised learning.
IBM J. Res. Dev., 2017
Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution.
CoRR, 2017
Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Exploiting local and generic features for accurate skin lesions classification using clinical and dermoscopy imaging.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
2016
Comput. Vis. Image Underst., 2016
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
2015
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015
2014
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014
Discriminative Multi-Task Sparse Learning for Robust Visual Tracking Using Conditional Random Field.
Proceedings of the 2014 International Conference on Digital Image Computing: Techniques and Applications, 2014
Proceedings of the 2014 International Conference on Digital Image Computing: Techniques and Applications, 2014
Enhanced Laplacian Group Sparse Learning with Lifespan Outlier Rejection for Visual Tracking.
Proceedings of the Computer Vision - ACCV 2014, 2014
2013
Proceedings of the Neural Information Processing - 20th International Conference, 2013
Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013
Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013
2012
Proceedings of the Neural Information Processing - 19th International Conference, 2012
2011
J. Signal Inf. Process., 2011