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Xiaoqin Zhang

Researcher at Wenzhou University

Publications -  145
Citations -  5163

Xiaoqin Zhang is an academic researcher from Wenzhou University. The author has contributed to research in topics: Video tracking & Computer science. The author has an hindex of 28, co-authored 135 publications receiving 3650 citations. Previous affiliations of Xiaoqin Zhang include Chinese Academy of Sciences.

Papers
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Journal ArticleDOI

Multiple object tracking: A literature review

TL;DR: This work provides a thorough review on the development of this problem in recent decades and inspects the recent advances in various aspects and proposes some interesting directions for future research.
Journal ArticleDOI

Enhanced Moth-flame optimizer with mutation strategy for global optimization

TL;DR: GM is introduced into the basic MFO to improve neighborhood-informed capability, CM with a large mutation step is adopted to enhance global exploration ability and LM is embedded to increase the randomness of search agents’ movement.
Posted Content

Multiple Object Tracking: A Literature Review

TL;DR: In this article, a comprehensive and most recent review on the state-of-the-art multiple object tracking (MOT) methods is presented, in which existing approaches are divided into different groups and each group is discussed in detail for the principles, advances and drawbacks.
Proceedings ArticleDOI

The Visual Object Tracking VOT2013 Challenge Results

TL;DR: The evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset are presented, offering a more systematic comparison of the trackers.
Journal ArticleDOI

Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection

TL;DR: This paper develops a GWO variant enhanced with a covariance matrix adaptation evolution strategy (CMAES), levy flight mechanism, and orthogonal learning (OL) strategy named GWOCMALOL, which could reach higher classification accuracy and fewer feature selections than other optimization algorithms.