15 citations · 22 across the 8 of their papers we have counts for
8 papers
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…
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…
Hierarchical Codebook Design and Analytical Beamforming Solution for IRS Assisted Communication
Xiyuan Liu, Qingqing Wu, Die Hu +2
In intelligent reflecting surface (IRS) assisted communication, beam search is usually time-consuming as the multiple-input multiple-output (MIMO) of IRS is usually very large. Hie…
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…
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…
Hybrid Interference Mitigation Using Analog Prewhitening
Wei Zhang, Yi Jiang, Bin Zhou +1
This paper proposes a novel scheme for mitigating strong interferences, which is applicable to various wireless scenarios, including full-duplex wireless communications and uncoord…
Learning Smooth Representation for Unsupervised Domain Adaptation
Guanyu Cai, Lianghua He, Mengchu Zhou +2
Typical adversarial-training-based unsupervised domain adaptation methods are vulnerable when the source and target datasets are highly-complex or exhibit a large discrepancy betwe…
A Scalable Framework for CSI Feedback in FDD Massive MIMO via DL Path Aligning
Xiliang Luo, Penghao Cai, Xiaoyu Zhang +2
Unlike the time-division duplexing (TDD) systems, the downlink (DL) and uplink (UL) channels are not reciprocal anymore in the case of frequency-division duplexing (FDD). However,…