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researcher

C. Fan

4 papers hereh-index 14609 citations106 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.SP2
  • cs.CV1
  • cs.NE1
same name
  • C. Fan — 5 papers, h 12
  • C. Fan — 4 papers, h 12
  • C. Fan — 2 papers, h 8
  • C. Fan — 2 papers, h 19
  • C. Fan — 2 papers, h 6
  • C. Fan — 1 paper, h 11

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedMultilevel Image Thresholding Using a Fully Informed Cuckoo Search Algorithm

3 citations · 3 across the 4 of their papers we have counts for

collaborators

4 papers

eess.SP2020

MIMO Radar Waveform-Filter Design for Extended Target Detection from a View of Games

Zhou Xu, Chongyi Fan, Xiaotao Huang

This paper studies the Two-Person Zero Sum(TPZS) game between a Multiple-Input Multiple-Output(MIMO) radar and an extended target with payoff function being the output Signal-to-In…

eess.SP2020

Robust MIMO Radar Waveform-Filter Design for Extended Target Detection in the Presence of Multipath

Zhou Xu, Chongyi Fan, Jian Wang +1

The existence of multipath brings extra "looks" of targets. This paper considers the extended target detection problem with a narrow band Multiple-Input Multiple-Output(MIMO) radar…

cs.NE2020★ 3 cited

Multilevel Image Thresholding Using a Fully Informed Cuckoo Search Algorithm

Xiaotao Huang, Liang Shen, Chongyi Fan +2

Though effective in the segmentation, conventional multilevel thresholding methods are computationally expensive as exhaustive search are used for optimal thresholds to optimize th…

cs.CV2019

Novel Co-variant Feature Point Matching Based on Gaussian Mixture Model

Liang Shen, Jiahua Zhu, Chongyi Fan +2

The feature frame is a key idea of feature matching problem between two images. However, most of the traditional matching methods only simply employ the spatial location informatio…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.