Image computing for fibre-bundle endomicroscopy: A review
Endomicroscopy is an emerging imaging modality, that facilitates the acquisition of in vivo, in
situ optical biopsies, assisting diagnostic and potentially therapeutic interventions. While …
situ optical biopsies, assisting diagnostic and potentially therapeutic interventions. While …
A graph-based semi-supervised reject inference framework considering imbalanced data distribution for consumer credit scoring
Y Kang, N Jia, R Cui, J Deng - Applied Soft Computing, 2021 - Elsevier
Credit scoring has been attracting increasing attention in the Chinese consumer financial
industry. Traditional approaches are easily influenced by sample selection bias because …
industry. Traditional approaches are easily influenced by sample selection bias because …
Improving classification of breast cancer by utilizing the image pyramids of whole-slide imaging and multi-scale convolutional neural networks
Whole-slide imaging (WSI) is the digitization of conventional glass slides. Automatic
computer-aided diagnosis (CAD) based on WSI enables digital pathology and the …
computer-aided diagnosis (CAD) based on WSI enables digital pathology and the …
CAESNet: Convolutional AutoEncoder based Semi-supervised Network for improving multiclass classification of endomicroscopic images
Objective This article presents a novel method of semisupervised learning using
convolutional autoencoders for optical endomicroscopic images. Optical endomicroscopy …
convolutional autoencoders for optical endomicroscopic images. Optical endomicroscopy …