activity
20172022
most citedSAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

94 citations · 127 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20201 cited

P-DIFF: Learning Classifier with Noisy Labels based on Probability Difference Distributions

Wei Hu, QiHao Zhao, Yangyu Huang +1

Learning deep neural network (DNN) classifier with noisy labels is a challenging task because the DNN can easily over-fit on these noisy labels due to its high capability. In this…

cs.LG20201 cited

Integrating global spatial features in CNN based Hyperspectral/SAR imagery classification

Fan Zhang, MinChao Yan, Chen Hu +2

The land cover classification has played an important role in remote sensing because it can intelligently identify things in one huge remote sensing image to reduce the work of hum…

cs.CV2018

SeqFace: Make full use of sequence information for face recognition

Wei Hu, Yangyu Huang, Fan Zhang +3

Deep convolutional neural networks (CNNs) have greatly improved the Face Recognition (FR) performance in recent years. Almost all CNNs in FR are trained on the carefully labeled da…

cs.CV201731 cited

DeepUNet: A Deep Fully Convolutional Network for Pixel-level Sea-Land Segmentation

Ruirui Li, Wenjie Liu, Lei Yang +4

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the sea-land segmentation is a challenging task. Al…

cs.CV201794 cited

SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

Fan Zhang, Chen Hu, Qiang Yin +3

The outstanding pattern recognition performance of deep learning brings new vitality to the synthetic aperture radar (SAR) automatic target recognition (ATR). However, there is a l…