4 citations · 19 across the 12 of their papers we have counts for
12 papers
PSHop: A Lightweight Feed-Forward Method for 3D Prostate Gland Segmentation
Yijing Yang, Vasileios Magoulianitis, Jiaxin Yang +8
Automatic prostate segmentation is an important step in computer-aided diagnosis of prostate cancer and treatment planning. Existing methods of prostate segmentation are based on d…
PCa-RadHop: A Transparent and Lightweight Feed-forward Method for Clinically Significant Prostate Cancer Segmentation
Vasileios Magoulianitis, Jiaxin Yang, Yijing Yang +8
Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increa…
Acceleration of Subspace Learning Machine via Particle Swarm Optimization and Parallel Processing
Hongyu Fu, Yijing Yang, Yuhuai Liu +4
Built upon the decision tree (DT) classification and regression idea, the subspace learning machine (SLM) has been recently proposed to offer higher performance in general classifi…
Statistical Attention Localization (SAL): Methodology and Application to Object Classification
Yijing Yang, Vasileios Magoulianitis, Xinyu Wang +1
A statistical attention localization (SAL) method is proposed to facilitate the object classification task in this work. SAL consists of three steps: 1) preliminary attention windo…
Design of Supervision-Scalable Learning Systems: Methodology and Performance Benchmarking
Yijing Yang, Hongyu Fu, C. -C. Jay Kuo
The design of robust learning systems that offer stable performance under a wide range of supervision degrees is investigated in this work. We choose the image classification probl…
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…
On Supervised Feature Selection from High Dimensional Feature Spaces
Yijing Yang, Wei Wang, Hongyu Fu +1
The application of machine learning to image and video data often yields a high dimensional feature space. Effective feature selection techniques identify a discriminant feature su…
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…