7 citations · 15 across the 5 of their papers we have counts for
7 papers
Nucleus Neural Network: A Data-driven Self-organized Architecture
Jia Liu, Maoguo Gong, Haibo He
Artificial neural networks which are inspired from the learning mechanism of brain have achieved great successes in many problems, especially those with deep layers. In this paper,…
Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning
Hong Huang, Guangyao Shi, Haibo He +2
The graph embedding (GE) methods have been widely applied for dimensionality reduction of hyperspectral imagery (HSI). However, a major challenge of GE is how to choose proper neig…
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach
Hao-Hsuan Chang, Hao Song, Yang Yi +3
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to share radio spectrum among different networks. As a secondary user (SU), a DSA device will fac…
A Local Density-Based Approach for Local Outlier Detection
Bo Tang, Haibo He
This paper presents a simple but effective density-based outlier detection approach with the local kernel density estimation (KDE). A Relative Density-based Outlier Score (RDOS) is…
Probabilistic Human Mobility Model in Indoor Environment
Bo Tang, Chao Jiang, Haibo He +1
Understanding human mobility is important for the development of intelligent mobile service robots as it can provide prior knowledge and predictions of human distribution for robot…
Kernel-based Generative Learning in Distortion Feature Space
Bo Tang, Paul M. Baggenstoss, Haibo He
This paper presents a novel kernel-based generative classifier which is defined in a distortion subspace using polynomial series expansion, named Kernel-Distortion (KD) classifier.…