3 citations · 4 across the 6 of their papers we have counts for
6 papers
Deep Clustering via Distribution Learning
Guanfang Dong, Zijie Tan, Chenqiu Zhao +1
Distribution learning finds probability density functions from a set of data samples, whereas clustering aims to group similar data points to form clusters. Although there are deep…
Medical Image Denosing via Explainable AI Feature Preserving Loss
Guanfang Dong, Anup Basu
Denoising algorithms play a crucial role in medical image processing and analysis. However, classical denoising algorithms often ignore explanatory and critical medical features pr…
Bridging Distribution Learning and Image Clustering in High-dimensional Space
Guanfang Dong, Chenqiu Zhao, Anup Basu
Distribution learning focuses on learning the probability density function from a set of data samples. In contrast, clustering aims to group similar objects together in an unsuperv…
Learning Distributions via Monte-Carlo Marginalization
Chenqiu Zhao, Guanfang Dong, Anup Basu
We propose a novel method to learn intractable distributions from their samples. The main idea is to use a parametric distribution model, such as a Gaussian Mixture Model (GMM), to…
Is Deep Learning Network Necessary for Image Generation?
Chenqiu Zhao, Guanfang Dong, Anup Basu
Recently, images are considered samples from a high-dimensional distribution, and deep learning has become almost synonymous with image generation. However, is a deep learning netw…
Real-time Street Human Motion Capture
Yanquan Chen, Fei Yang, Tianyu Lang +2
In recent years, motion capture technology using computers has developed rapidly. Because of its high efficiency and excellent performance, it replaces many traditional methods and…