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Guanghui He
Researcher at Shanghai Jiao Tong University
Publications - 58
Citations - 525
Guanghui He is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: MIMO & Computer science. The author has an hindex of 9, co-authored 48 publications receiving 334 citations.
Papers
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Journal ArticleDOI
A Near-Optimal Detection Scheme Based on Joint Steepest Descent and Jacobi Method for Uplink Massive MIMO Systems
TL;DR: Simulation results show that the proposed method outperforms Neumann Series, Richardson method, and conjugate gradient based methods, while achieving the near-optimal performance of linear detectors with a small number of iterations.
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Scale Adaptive Proposal Network for Object Detection in Remote Sensing Images
TL;DR: Comparative experimental results show that the proposed SAPNet significantly improves the accuracy of multiobject detection.
Journal ArticleDOI
VLSI Implementation of a High-Throughput Iterative Fixed-Complexity Sphere Decoder
Xi Chen,Guanghui He,Jun Ma +2 more
TL;DR: A soft-input soft-output fixed-complexity-sphere-decoding algorithm and its very large scale integration architecture are proposed for the iterative MIMO receiver and its deeply pipelined architecture improves the detection performance significantly with low detection latency.
Journal ArticleDOI
Design and Implementation of Flexible Dual-Mode Soft-Output MIMO Detector With Channel Preprocessing
TL;DR: A flexible dual-mode soft-output multiple-input multiple-output (MIMO) detector to support open-loop and closed-loop in Chinese enhanced ultra high throughput (EUHT) wireless local area network (LAN) standard is proposed.
Journal ArticleDOI
Ship detection based on fused features and rebuilt YOLOv3 networks in optical remote-sensing images
Qin Wang,Fengyi Shen,Lifu Cheng,Jianfei Jiang,Guanghui He,Weiguang Sheng,Naifeng Jing,Zhigang Mao +7 more
TL;DR: This work proposes a ship-detection method based on a deep convolutional neural network that is modified from YOLOv3 that has strong robustness and can adapt to complex environments like inshore ship detection.