Jongseong Jang | DeepAI

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∙ 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...

0 Jongseong Jang, et al. ∙

∙ 03/14/2022

TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation

Weakly supervised semantic segmentation (WSSS) with only image-level sup...

0 Ruiwen Li, et al. ∙

∙ 11/28/2021

ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification

Contrastive learning has led to substantial improvements in the quality ...

0 Zhibo Zhang, et al. ∙

∙ 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...

0 Changhwan Lee, et al. ∙

∙ 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...

0 Ruiwen Li, et al. ∙

∙ 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...

0 Sam Sattarzadeh, et al. ∙

∙ 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...

0 Mahesh Sudhakar, et al. ∙

∙ 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 ...

0 Sam Sattarzadeh, et al. ∙

∙ 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...

14 Zheda Mai, et al. ∙

∙ 09/19/2019

Propagated Perturbation of Adversarial Attack for well-known CNNs: Empirical Study and its Explanation

Deep Neural Network based classifiers are known to be vulnerable to pert...

0 Jihyeun Yoon, et al. ∙

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