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20222024
most citedVisual Neural Decoding via Improved Visual-EEG Semantic Consistency

2 citations · 2 across the 7 of their papers we have counts for

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7 papers

cs.CV2024★ 2 cited

Visual Neural Decoding via Improved Visual-EEG Semantic Consistency

Hongzhou Chen, Lianghua He, Yihang Liu +3

Visual neural decoding aims to extract and interpret original visual experiences directly from human brain activity. Recent studies have demonstrated the feasibility of decoding vi…

cs.CV2024

Hierarchical Salient Patch Identification for Interpretable Fundus Disease Localization

Yitao Peng, Lianghua He, Die Hu

With the widespread application of deep learning technology in medical image analysis, the effective explanation of model predictions and improvement of diagnostic accuracy have be…

cs.CV2023

FeaInfNet: Diagnosis in Medical Image with Feature-Driven Inference and Visual Explanations

Yitao Peng, Lianghua He, Die Hu +3

Interpretable deep learning models have received widespread attention in the field of image recognition. Due to the unique multi-instance learning of medical images and the difficu…

cs.CV2023

Hierarchical Dynamic Masks for Visual Explanation of Neural Networks

Yitao Peng, Longzhen Yang, Yihang Liu +1

Saliency methods generating visual explanatory maps representing the importance of image pixels for model classification is a popular technique for explaining neural network decisi…

cs.CV2022

Decoupling Deep Learning for Interpretable Image Recognition

Yitao Peng, Yihang Liu, Longzhen Yang +1

The interpretability of neural networks has recently received extensive attention. Previous prototype-based explainable networks involved prototype activation in both reasoning and…

cs.CV2022

MDM: Multiple Dynamic Masks for Visual Explanation of Neural Networks

Yitao Peng, Longzhen Yang, Yihang Liu +1

The Class Activation Map (CAM) lookup of a neural network tells us to which regions the neural network focuses when it makes a decision. In the past, the CAM search method was depe…

cs.CV2022

Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning

Longzhen Yang, Yihang Liu, Yitao Peng +1

Accuracy and Diversity are two essential metrizable manifestations in generating natural and semantically correct captions. Many efforts have been made to enhance one of them with…