2.7k citations · 3.4k across the 32 of their papers we have counts for
5 papers · 2 filters
ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks
Xiaodan Hu, Audrey G. Chung, Paul Fieguth +3
Generative Adversarial Networks (GANs) have shown considerable promise for mitigating the challenge of data scarcity when building machine learning-driven analysis algorithms. Spec…
Mitigating Architectural Mismatch During the Evolutionary Synthesis of Deep Neural Networks
Audrey Chung, Paul Fieguth, Alexander Wong
Evolutionary deep intelligence has recently shown great promise for producing small, powerful deep neural network models via the organic synthesis of increasingly efficient archite…
Deep Learning for Generic Object Detection: A Survey
Li Liu, Wanli Ouyang, Xiaogang Wang +4
Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural…
Texture Classification in Extreme Scale Variations using GANet
Li Liu, Jie Chen, Guoying Zhao +3
Research in texture recognition often concentrates on recognizing textures with intraclass variations such as illumination, rotation, viewpoint and small scale changes. In contrast…
From BoW to CNN: Two Decades of Texture Representation for Texture Classification
Li Liu, Jie Chen, Paul Fieguth +3
Texture is a fundamental characteristic of many types of images, and texture representation is one of the essential and challenging problems in computer vision and pattern recognit…