An implementation of optimized framework for action classification using multilayers neural network on selected fused features-Reference-Cited by-同舟云学术

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An implementation of optimized framework for action classification using multilayers neural network on selected fused features

Published:2018-01-27 Issue:4 Volume:22 Page:1377-1397
ISSN:1433-7541
Container-title:Pattern Analysis and Applications
language:en
Short-container-title:Pattern Anal Applic

Author:

Khan Muhammad Attique,Akram Tallha,Sharif Muhammad,Javed Muhammad Younus,Muhammad Nazeer,Yasmin Mussarat

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition

Link

http://link.springer.com/article/10.1007/s10044-018-0688-1/fulltext.html

Reference71 articles.

1. Ye Q, Han Z, Jiao J, Liu J (2013) Human detection in images via piecewise linear support vector machines. IEEE Trans Image Process 22(2):778–789

2. Liang C-W, Juang C-F (2015) Moving object classification using local shape and HOG features in wavelet-transformed space with hierarchical SVM classifiers. Appl Soft Comput 28:483–497

3. Xu Y, Dong X, Lin S, Han TX, Cao X, Li X (2012) Detection of sudden pedestrian crossings for driving assistance systems. IEEE Trans Syst Man Cybern B Cybern 42(3):729–739

4. Juang C-F, Chang C-M (2007) Human body posture classification by a neural fuzzy network and home care system application. IEEE Trans Syst Man Cybern Part A Syst Hum 37(6):984–994

5. Ye Q, Liang J, Jiao J (2012) Pedestrian detection in video images via error correcting output code classification of manifold subclasses. IEEE Trans Intell Transp Syst 13(1):193–202

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