5 citations · 14 across the 12 of their papers we have counts for
17 papers
Point Cloud Attribute Compression via Successive Subspace Graph Transform
Yueru Chen, Yiting Shao, Jing Wang +2
Inspired by the recently proposed successive subspace learning (SSL) principles, we develop a successive subspace graph transform (SSGT) to address point cloud attribute compressio…
PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model for Image Classification
Yueru Chen, Mozhdeh Rouhsedaghat, Suya You +2
The successive subspace learning (SSL) principle was developed and used to design an interpretable learning model, known as the PixelHop method,for image classification in our prio…
PixelHop: A Successive Subspace Learning (SSL) Method for Object Classification
Yueru Chen, C. -C. Jay Kuo
A new machine learning methodology, called successive subspace learning (SSL), is introduced in this work. SSL contains four key ingredients: 1) successive near-to-far neighborhood…
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…
Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks
Ye Wang, Yueru Chen, Jongmoo Choi +1
This paper reports a visible and thermal drone monitoring system that integrates deep-learning-based detection and tracking modules. The biggest challenge in adopting deep learning…