papers

Publications (7)

cs.CV2018

Tubule segmentation of fluorescence microscopy images based on convolutional neural networks with inhomogeneity correction

Soonam Lee, Chichen Fu, Paul Salama +2

Fluorescence microscopy has become a widely used tool for studying various biological structures of in vivo tissue or cells. However, quantitative analysis of these biological stru…

cs.CV2018

Texture Segmentation Based Video Compression Using Convolutional Neural Networks

Chichen Fu, Di Chen, Edward J. Delp +2

There has been a growing interest in using different approaches to improve the coding efficiency of modern video codec in recent years as demand for web-based video consumption inc…

eess.IV2019

Center-Extraction-Based Three Dimensional Nuclei Instance Segmentation of Fluorescence Microscopy Images

David Joon Ho, Shuo Han, Chichen Fu +3

Fluorescence microscopy is an essential tool for the analysis of 3D subcellular structures in tissue. An important step in the characterization of tissue involves nuclei segmentati…

cs.CV2018

Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation

Chichen Fu, Soonam Lee, David Joon Ho +4

Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characte…

eess.IV2019

Convolutional Neural Networks Based Texture Modeling For AV1

Di Chen, Chichen Fu, Zoe Liu +1

Modern video codecs including the newly developed AOMedia Video 1 (AV1) utilize hybrid coding techniques to remove spatial and temporal redundancy. However, efficient exploitation…

cs.CV2018

Single-View Food Portion Estimation: Learning Image-to-Energy Mappings Using Generative Adversarial Networks

Shaobo Fang, Zeman Shao, Runyu Mao +5

Due to the growing concern of chronic diseases and other health problems related to diet, there is a need to develop accurate methods to estimate an individual's food and energy in…