4 citations · 11 across the 6 of their papers we have counts for
6 papers
Subspace Learning Machine (SLM): Methodology and Performance
Hongyu Fu, Yijing Yang, Vinod K. Mishra +1
Inspired by the feedforward multilayer perceptron (FF-MLP), decision tree (DT) and extreme learning machine (ELM), a new classification model, called the subspace learning machine…
HUNIS: High-Performance Unsupervised Nuclei Instance Segmentation
Vasileios Magoulianitis, Yijing Yang, C. -C. Jay Kuo
A high-performance unsupervised nuclei instance segmentation (HUNIS) method is proposed in this work. HUNIS consists of two-stage block-wise operations. The first stage includes: 1…
Unsupervised Data-Driven Nuclei Segmentation For Histology Images
Vasileios Magoulianitis, Peida Han, Yijing Yang +1
An unsupervised data-driven nuclei segmentation method for histology images, called CBM, is proposed in this work. CBM consists of three modules applied in a block-wise manner: 1)…
E-PixelHop: An Enhanced PixelHop Method for Object Classification
Yijing Yang, Vasileios Magoulianitis, C. -C. Jay Kuo
Based on PixelHop and PixelHop++, which are recently developed using the successive subspace learning (SSL) framework, we propose an enhanced solution for object classification, ca…
Semi-supervised learning via Feedforward-Designed Convolutional Neural Networks
Yueru Chen, Yijing Yang, Min Zhang +1
A semi-supervised learning framework using the feedforward-designed convolutional neural networks (FF-CNNs) is proposed for image classification in this work. One unique property o…
Ensembles of feedforward-designed convolutional neural networks
Yueru Chen, Yijing Yang, Wei Wang +1
An ensemble method that fuses the output decision vectors of multiple feedforward-designed convolutional neural networks (FF-CNNs) to solve the image classification problem is prop…