L 1 norm based pedestrian detection using video analytics technique-Reference-Cited by-同舟云学术

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L 1 norm based pedestrian detection using video analytics technique

Published:2020-02-22 Issue:4 Volume:36 Page:1569-1579
ISSN:0824-7935
Container-title:Computational Intelligence
language:en
Short-container-title:Computational Intelligence

Author:

Selvaraj Anandamurugan¹,Selvaraj Jeeva¹²^ORCID,Maruthaiappan Sivabalakrishnan²,Babu Gokulnath Chandra³,Kumar Priyan Malarvizhi⁴^ORCID

Affiliation:

1. Department of Information Technology Kongu Engineering College Erode India

2. School of Computing Science and Engineering VIT Chennai India

3. School of Computing Science and Engineering VIT Vellore India

4. Department of CSE Middlesex University London UK

Publisher

Wiley

Subject

Artificial Intelligence,Computational Mathematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12292

Reference16 articles.

1. Dibra E.2013.Robust people detection using computer vision(Master's thesis). ETH Zurich.

2. Speech recognition with improved support vector machine using dual classifiers and cross fitness validation

3. A Real-time Pedestrian Detection based on AGMM and HOG for Embedded Surveillance

4. Optimal feature selection for pedestrian detection based on logistic regression analysis;Kim J;IEEE Int Conf Syst Man Cybernet,2013

5. Optimal body mass index cutoff point for cardiovascular disease and high blood pressure

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3. ConvGRU-CNN: Spatiotemporal Deep Learning for Real-World Anomaly Detection in Video Surveillance System;International Journal of Interactive Multimedia and Artificial Intelligence;2023

4. E2E-VSDL: End-to-end video surveillance-based deep learning model to detect and prevent criminal activities;Image and Vision Computing;2022-07

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