research
∙
12/14/2022
Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders
Deep neural networks have been successfully adopted to diverse domains i...
share
research
∙
03/14/2022
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation (WSSS) with only image-level sup...
research
∙
11/28/2021
ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification
Contrastive learning has led to substantial improvements in the quality ...
research
∙
11/25/2021
Look at here : Utilizing supervision to attend subtle key regions
Despite the success of deep learning in computer vision, algorithms to r...
research
∙
05/29/2021
EDDA: Explanation-driven Data Augmentation to Improve Model and Explanation Alignment
Recent years have seen the introduction of a range of methods for post-h...
research
∙
02/15/2021
Integrated Grad-CAM: Sensitivity-Aware Visual Explanation of Deep Convolutional Networks via Integrated Gradient-Based Scoring
Visualizing the features captured by Convolutional Neural Networks (CNNs...
research
∙
02/15/2021
Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks
Explainable AI (XAI) is an active research area to interpret a neural ne...
research
∙
10/01/2020
Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation
As an emerging field in Machine Learning, Explainable AI (XAI) has been ...
research
∙
08/31/2020
Adversarial Shapley Value Experience Replay for Task-Free Continual Learning
Continual learning is a branch of deep learning that seeks to strike a b...
research
∙
09/19/2019