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SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019, p.2710-2719

2019

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DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

EURASIP journal on image and video processing, 2019-07, Vol.2019 (1), p.1-10, Article 71

2019

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Image super-resolution using progressive generative adversarial networks for medical image analysis

Computerized medical imaging and graphics, 2019-01, Vol.71, p.30-39

2019

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Editorial: Computational Pathology

Frontiers in medicine, 2020-06, Vol.7, p.245-245

2020

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MSMCT: Multi-State Multi-Camera Tracker

IEEE transactions on circuits and systems for video technology, 2018-12, Vol.28 (12), p.3361-3376

2018

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ExprADA: Adversarial domain adaptation for facial expression analysis

Pattern recognition, 2020-04, Vol.100, p.107111, Article 107111

2020

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Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

IEEE transactions on medical imaging, 2021-10, Vol.40 (10), p.2926-2938

2021

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GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Medical image analysis, 2024-04, Vol.93, p.103075-103075, Article 103075

2024

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Efficient multi-target tracking via discovering dense subgraphs

Computer vision and image understanding, 2016-03, Vol.144, p.205-216

2016

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Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.9608-9617

2020

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Enhanced Laplacian Group Sparse Learning with Lifespan Outlier Rejection for Visual Tracking

Computer Vision -- ACCV 2014, p.564-578

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Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

IEEE transactions on medical imaging, 2024-05, Vol.43 (5), p.2021-2032

2024

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Weakly supervised joint whole-slide segmentation and classification in prostate cancer

Medical image analysis, 2023-10, Vol.89, p.102915-102915, Article 102915

2023

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ALFREDO: Active Learning with FeatuRe disEntangelement and DOmain adaptation for medical image classification

Medical image analysis, 2024-10, Vol.97, p.103261, Article 103261

2024

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Medical Image Classification Using Generalized Zero Shot Learning

2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021, p.3337-3346

2021

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Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Computer vision and image understanding, 2019-07, Vol.184, p.57-65

2019

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Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

Medical image analysis, 2022-07, Vol.79, p.102473-102473, Article 102473

2022

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Learn to synthesize and synthesize to learn

Computer vision and image understanding, 2019-08, Vol.185, p.1-11

2019

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Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime

Computers in biology and medicine, 2024-02, Vol.169, p.107809-107809, Article 107809

2024

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Quantifying Explainers of Graph Neural Networks in Computational Pathology

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.8102-8112

2021

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SaGTTA: Saliency Guided Test Time Augmentation for Medical Image Segmentation Across Vendor Domain Shift

2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023, p.1-4

2023

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TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.20341-20350

2023

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ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023, p.6159-6168

2023

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Benefiting from multitask learning to improve single image super-resolution

Neurocomputing (Amsterdam), 2020-07, Vol.398, p.304-313

2020

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The Visual Object Tracking VOT2013 Challenge Results

2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW), 2013, p.98-111

2013

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SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

Image super-resolution using progressive generative adversarial networks for medical image analysis

Editorial: Computational Pathology

MSMCT: Multi-State Multi-Camera Tracker

ExprADA: Adversarial domain adaptation for facial expression analysis

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Efficient multi-target tracking via discovering dense subgraphs

Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

Enhanced Laplacian Group Sparse Learning with Lifespan Outlier Rejection for Visual Tracking

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

Weakly supervised joint whole-slide segmentation and classification in prostate cancer

ALFREDO: Active Learning with FeatuRe disEntangelement and DOmain adaptation for medical image classification

Medical Image Classification Using Generalized Zero Shot Learning

Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

Learn to synthesize and synthesize to learn

Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime

Quantifying Explainers of Graph Neural Networks in Computational Pathology

SaGTTA: Saliency Guided Test Time Augmentation for Medical Image Segmentation Across Vendor Domain Shift

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

Benefiting from multitask learning to improve single image super-resolution

The Visual Object Tracking VOT2013 Challenge Results

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