VEHICLE DETECTION AND TRACKING USING MACHINE LEARNING TECHNIQUES AS SUPPORT VECTOR MACHINE
DOI:
https://doi.org/10.59367/zywpck72Keywords:
Vehicle detection, Vehicle Tracking, SVM, Decision Tree, Image detectionAbstract
Machine learning can be used to detect and classify objects in images and videos. Vehicle detection, is basically the scientific methods and ways of how machines see rather than human eyes. Vehicle detection is one of the widely used features by companies and organizations these days. We can use computer vision to detect different types of vehicles in a video or real-time via a camera. Vehicle detection and tracking finds its applications in traffic control, car tracking, creating parking sensors and many more. Python programming language is very user friendly language that have been utilized as the development language for the creation. The Support VectorMachine (SVM) and Decision tree are the two algorithms have been developed, trained, tested, and compared to each other, although suggest the best model among these two.
References
Yang H. et al.”Real-time vehicle detection and counting in complex traffic scenes using background subtraction model with low-rank decomposition”IET Intell Transp Syst(2018)
Chirag,”Vehicle Detection And Tracking Using Machine Learning Techniques” IJCRT | Volume 11, Issue 4 April 2023 | ISSN: 2320-2882
Sonal S. Chaudhari,” Vehicle Detection and Tracking by SVM improving surveillance system efficiency”International Journal of Research in Advent Technology, Vol.6, No.1, January 2018 E-ISSN: 2321-9637
Dr. N.Raj kumar ,”Svm classifier for vehicle surveillance Under nighttime video scenes”,IRACS- (IJCSITS),ISSN: 2249-9555, Vol. 2, No. 1, 2012T. vol. 42, no. 7, pp. 1297–1307, Jul. 2009.
M. Cheon,W. Lee, C. Yoon, andM. Park, “Vision-based vehicle detection system with consideration ofthe detecting location,”‖ IEEE Trans. Intell. Transp.Syst., vol. 13, no. 3, pp. 1243–1252, Sep. 2012
V.Sowmya1*, R.Radha,” Heavy-Vehicle Detection Using SVM and HOG Features”
International Journal of Computer Sciences and Engineering Open Access Research Paper Vol.-7, Special Issue, 5, March 2019 E-ISSN: 2347-2693
Stephen Karungaru, Lyu Dongyang, and Kenji Terada,”Vehicle Detection and Type Classification Based on CNN-SVM” International Journal of Machine Learning and Computing, Vol. 11, No. 4, July 2021
Mahesh Suryawanshi*1, Akash Ghadage*2 ,”A Video Based Vehicle Detection, Counting And Classification System”e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science ( Peer-Reviewed, Open Access, Fully Refereed International Journal ) Volume:04/Issue:06/June-2022 Impact Factor- 6.752
Suruchi Kumari, Deepti Agrawal,” Video Based Vehicle Detection and Tracking using Image Processing”,International Journal of Research Publication and Reviews, Vol 3, no 8, pp 735-742, August 2022
Bhagya S Hadagalimath, Ayesha Siddiqui, Dr. Suvarna Nandya ,”Classification and Counting of Vehicle using Image Processing Techniques " jraset Journal For Research in Applied Science and Engineering Technology. 2022-12-26 ISSN : 2321-9653
Lowlesh Nandkishor Yadav, “Predictive Acknowledgement using TRE System to reduce cost and Bandwidth”IJRECE VOL. 7 ISSUE 1 (JANUARY- MARCH 2019) pg no 275-278
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Futuristic Innovation in Arts, Humanities and Management (IJFIAHM)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.