A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy-Reference-Cited by-同舟云学术

A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy

Published:2017-02-24 Issue:3 Volume:32 Page:1775-1786
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Hu Keli¹,Ye Jun¹,Fan En¹,Shen Shigen¹,Huang Longjun¹,Pi Jiatian²

Affiliation:

1. Department of Computer Science and Engineering, Shaoxing University, Shaoxing, Zhejiang, China

2. Key Laboratory of Wireless Sensor Network and Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference35 articles.

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3. Robust object tracking with online multiple instance learning;Babenko;IEEE Transactions on Pattern Analysis and Machine Intelligence,2011

4. TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment;Biswas;Neural Computing and Applications,2015

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