An accurate foreground moving object detection based on segmentation techniques and optimal classifier-Reference-Cited by-同舟云学术

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An accurate foreground moving object detection based on segmentation techniques and optimal classifier

Published:2021-11-03 Issue:5 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Nagaraju Melam¹^ORCID,Babu B. Sobhan²,Sai Somayajulu Meduri V. N. S. S. R. K.¹,Sarma K. Subrahmanya Kousik¹,Vetagiri Advaitha³

Affiliation:

1. Department of Information Technology Gudlavalleru Engineering College Gudlavalleru India

2. Department of Computer Science and Engineering Krishna University College of Engineering Machilipatnam India

3. Department of Computer Science and Engineering Gudlavalleru Engineering College Gudlavalleru India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6689

Reference28 articles.

1. Total Variation Regularized RPCA for Irregularly Moving Object Detection Under Dynamic Background

2. LemleyJ KarA CorcoranP.Eye tracking in augmented spaces: a deep learning approach. Proceedings of the 2018 IEEE Games Entertainment Media Conference (GEM); 2018:1‐6; IEEE.

3. Deep Learning with Unsupervised Data Labeling for Weed Detection in Line Crops in UAV Images

4. GomezA SigristL SchalchT BeniniL ThieleL.Wearable energy‐opportunistic vision sensing for walking speed estimation. Proceedings of the Sensors Applications Symposium (SAS); 2017:1‐6.

5. New Fuzzy Texture Features for Robust Detection of Moving Objects

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