X
Xiaohui Yuan
Researcher at University of North Texas
Publications - 187
Citations - 4320
Xiaohui Yuan is an academic researcher from University of North Texas. The author has contributed to research in topics: Computer science & Support vector machine. The author has an hindex of 28, co-authored 168 publications receiving 2828 citations. Previous affiliations of Xiaohui Yuan include National Institutes of Health & China University of Geosciences (Wuhan).
Papers
More filters
Journal ArticleDOI
Feature selection based on artificial bee colony and gradient boosting decision tree
Haidi Rao,Xianzhang Shi,Ahoussou Kouassi Rodrigue,Juanjuan Feng,Yingchun Xia,Mohamed Elhoseny,Xiaohui Yuan,Lichuan Gu +7 more
TL;DR: Experimental results demonstrate that the proposed feature selection method effectively reduces the dimensions of the dataset and achieves superior classification accuracy using the selected features.
Journal ArticleDOI
A review of deep learning methods for semantic segmentation of remote sensing imagery
TL;DR: A summary of the fundamental deep neural network architectures and the most recent developments of deep learning methods for semantic segmentation of remote sensing imagery including non-conventional data such as hyperspectral images and point clouds are reviewed.
Journal ArticleDOI
A Genetic Algorithm-Based, Dynamic Clustering Method Towards Improved WSN Longevity
TL;DR: A genetic algorithm-based, self-organizing network clustering (GASONeC) method that provides a framework to dynamically optimize wireless sensor node clusters and greatly extends the network life and the improvement up to 43.44 %.
Journal ArticleDOI
Fast Image Dehazing Method Based on Linear Transformation
TL;DR: A fast algorithm for single image dehazing is proposed based on linear transformation by assuming that a linear relationship exists in the minimum channel between the hazy image and the haze-free image, which can clearly and naturally recover the image.
Journal ArticleDOI
Balancing Energy Consumption in Heterogeneous Wireless Sensor Networks Using Genetic Algorithm
TL;DR: A Genetic Algorithm based method that optimizes heterogeneous sensor node clustering and greatly extends the network life, and the average improvement with respect to the second best performance based on the first-node-die and the last- node-die is 33.8% and 13%, respectively.