Y
Yin Zhang
Researcher at University of Electronic Science and Technology of China
Publications - 322
Citations - 7094
Yin Zhang is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Radar & Radar imaging. The author has an hindex of 35, co-authored 273 publications receiving 4960 citations. Previous affiliations of Yin Zhang include Huazhong University of Science and Technology & Nanjing University.
Papers
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Book ChapterDOI
Big Data Analysis
TL;DR: This chapter introduces the methods, architectures and tools for big data analysis, which mainly involves analytical methods for traditional data and big data, analytical architecture forbig data, and software used for mining and analysis of big data.
Journal ArticleDOI
Heuristic Path Planning Method for Multistatic UAV-Borne SAR Imaging System
TL;DR: In this paper, a constrained multiobjective optimization problem (CMOP) was proposed to solve the path planning problem of a multistatic UAV-SAR imaging system.
Journal ArticleDOI
Erratum to: Smart pathological brain detection system by predator-prey particle swarm optimization and single-hidden layer neural-network
TL;DR: An artificial intelligence and computer-aided diagnosis system that assists neuroradiologists to interpret magnetic resonance (MR) images, and a novel predator-prey particle swarm optimization (PP-PSO) algorithm used to train the weights of single-hidden layer neural-network (SLN).
Journal ArticleDOI
Target Fast Reconstruction of Real Aperture Radar Using Data Extrapolation-Based Parallel Iterative Adaptive Approach
TL;DR: In this article, a data extrapolation-based parallel iterative adaptive approach is proposed to fast reconstruct the targets in the whole sector without the distortion at the scene edge, where the echo model of RAR is repaired to remedy the model error.
Proceedings ArticleDOI
Data Analytics for the COVID-19 Epidemic
TL;DR: This paper presents a parameter learning method using particle swarm optimization and the least squares method, and uses it to predict the trend of the epidemic, and proposes an explainable fake news detection technique based on a variety of data mining methods.