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07/24/2023
AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays
Unsupervised anomaly detection in medical images such as chest radiograp...
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07/10/2023
Source-Free Open-Set Domain Adaptation for Histopathological Images via Distilling Self-Supervised Vision Transformer
There is a strong incentive to develop computational pathology models to...
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03/23/2023
Adaptive Similarity Bootstrapping for Self-Distillation
Most self-supervised methods for representation learning leverage a cros...
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03/23/2023
CrOC: Cross-View Online Clustering for Dense Visual Representation Learning
Learning dense visual representations without labels is an arduous task ...
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03/17/2023
TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation
Most recent test-time adaptation methods focus on only classification ta...
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02/10/2023
Self-Supervised Learning-Based Cervical Cytology Diagnostics in Low-Data Regime and Low-Resource Setting
Screening Papanicolaou test samples effectively reduces cervical cancer-...
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01/07/2023
Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer
The segmentation and automatic identification of histological regions of...
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02/15/2022
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification
Progress in digital pathology is hindered by high-resolution images and ...
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10/05/2021
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
In medical image segmentation, supervised deep networks' success comes a...
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08/20/2021
Self-Rule to Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection
Supervised learning is constrained by the availability of labeled data, ...
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04/06/2021
Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images
Existing reference (RF)-based super-resolution (SR) models try to improv...
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03/05/2021
Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation
Despite the successes of deep neural networks on many challenging vision...
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03/04/2021
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
Segmenting histology images into diagnostically relevant regions is impe...
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02/19/2021
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays
Detecting anomalies in musculoskeletal radiographs is of paramount impor...
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11/25/2020
Quantifying Explainers of Graph Neural Networks in Computational Pathology
Explainability of deep learning methods is imperative to facilitate thei...
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10/19/2020
Anomaly Detection on X-Rays Using Self-Supervised Aggregation Learning
Deep anomaly detection models using a supervised mode of learning usuall...
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08/05/2020
Structure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance
Although generative adversarial network (GAN) based style transfer is st...
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07/07/2020
Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer
With the long-term rapid increase in incidences of colorectal cancer (CR...
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07/06/2020
Benefitting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution
Super-resolution (SR) has traditionally been based on pairs of high-reso...
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03/31/2020
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation
Medical image segmentation is an important task for computer aided diagn...
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12/05/2019
Revisiting Few-Shot Learning for Facial Expression Recognition
Most of the existing deep neural nets on automatic facial expression rec...
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08/20/2019
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution
By benefiting from perceptual losses, recent studies have improved signi...
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07/29/2019
Benefiting from Multitask Learning to Improve Single Image Super-Resolution
Despite significant progress toward super resolving more realistic image...
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07/23/2019
Exploring Factors for Improving Low Resolution Face Recognition
State-of-the-art deep face recognition approaches report near perfect pe...
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05/17/2019
Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis
Cross-domain synthesizing realistic faces to learn deep models has attra...
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05/01/2019
Learn to synthesize and synthesize to learn
Attribute guided face image synthesis aims to manipulate attributes on a...
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04/24/2019
Informative sample generation using class aware generative adversarial networks for classification of chest Xrays
Training robust deep learning (DL) systems for disease detection from me...
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02/06/2019
Progressive Generative Adversarial Networks for Medical Image Super resolution
Anatomical landmark segmentation and pathology localization are importan...
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11/09/2018
Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks
We introduce a new scene graph generation method called image-level atte...
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06/14/2018
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network
Training robust deep learning (DL) systems for medical image classificat...
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10/13/2017