61 citations · 93 across the 5 of their papers we have counts for
6 papers · 1 filter
Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training
Xianxu Hou, Ke Sun, Linlin Shen +1
We present a new method for improving the performances of variational autoencoder (VAE). In addition to enforcing the deep feature consistent principle thus ensuring the VAE output…
Look, Investigate, and Classify: A Deep Hybrid Attention Method for Breast Cancer Classification
Bolei Xu, Jingxin Liu, Xianxu Hou +6
One issue with computer based histopathology image analysis is that the size of the raw image is usually very large. Taking the raw image as input to the deep learning model would…
Texture Deformation Based Generative Adversarial Networks for Face Editing
WenTing Chen, Xinpeng Xie, Xi Jia +1
Despite the significant success in image-to-image translation and latent representation based facial attribute editing and expression synthesis, the existing approaches still have…
Active Learning for Breast Cancer Identification
Xinpeng Xie, Yuexiang Li, Linlin Shen
Breast cancer is the second most common malignancy among women and has become a major public health problem in current society. Traditional breast cancer identification requires ex…
Skin Lesion Classification using Class Activation Map
Xi Jia, Linlin Shen
We proposed a two stage framework with only one network to analyze skin lesion images, we firstly trained a convolutional network to classify these images, and cropped the import r…
LOAD: Local Orientation Adaptive Descriptor for Texture and Material Classification
Xianbiao Qi, Guoying Zhao, Linlin Shen +2
In this paper, we propose a novel local feature, called Local Orientation Adaptive Descriptor (LOAD), to capture regional texture in an image. In LOAD, we proposed to define point…