Human Illegal Activity Recognition Based on Deep Learning Techniques-Reference-Cited by-同舟云学术

Human Illegal Activity Recognition Based on Deep Learning Techniques

Published:2023-02-24 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS)
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Author:

Shivaprasad Yadav S G¹,Itagi Sumangala²,Krishna Suresh B V N V³,K.L Hemalatha⁴,A C Ramachandra⁵

Affiliation:

1. Ramaiah Institute of Technology,Department of Electronics and Telecommunication Engineering,Bangalore,India

2. H. K. E. Society's S. L. N. College of Engineering,Department of Computer Science & Engineering,Raichur,India

3. K L University Vadeeshwaram,Department of Computer Science & Engineering,Vijayawada,India

4. Sri Krishna Institute of Technology,Department of Information Science and Engineering,Bangalore,India

5. Nitte Meenakshi Institute of Technology,Department of Electronics and Communication Engineering,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099473/10099480/10099857.pdf?arnumber=10099857

Reference15 articles.

1. A Survey of 3D Ear Recognition Techniques;iyyakutti iyappan;ACM Computing Surveys,2023

2. Optimal Time-Window Derivation for Human-Activity Recognition Based on Convolutional Neural Networks of Repeated Rehabilitation Motions

3. Transfer Learning Enhanced Vision-based Human Activity Recognition: A Decade-long Analysis;abhisek;International Journal of Information Management Data Insights,2023

4. IntOPMICM: Intelligent Medical Image Size Reduction Model;kumar pareek;Journal of Healthcare Engineering,2022

5. A Survey of 3D Ear Recognition Techniques;iyyakutti iyappan;ACM Computing Surveys,2023

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