Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers

1 code implementation • 4 Dec 2021 • Renzhen Wang, De Cai, Kaiwen Xiao, Xixi Jia, Xiao Han, Deyu Meng

Existing methods commonly address hierarchical classification by decoupling it into a series of multi-class classification tasks.

Classification Multi-class Classification +1

Blind deblurring for microscopic pathology images using deep learning networks

no code implementations • 24 Nov 2020 • Cheng Jiang, Jun Liao, Pei Dong, Zhaoxuan Ma, De Cai, Guoan Zheng, Yueping Liu, Hong Bu, Jianhua Yao

Artificial Intelligence (AI)-powered pathology is a revolutionary step in the world of digital pathology and shows great promise to increase both diagnosis accuracy and efficiency.

Deblurring

Adaptive Weighting Depth-variant Deconvolution of Fluorescence Microscopy Images with Convolutional Neural Network

no code implementations • 7 Jul 2019 • Da He, De Cai, Jiasheng Zhou, Jiajia Luo, Sung-Liang Chen

The adaptive weighting of the patch-wise deconvolved image can eliminate patch boundary artifacts and improve deconvolved image quality.