a24cd620-1731-444f-aa8c-86df39ac96de20230306090506264naun:naunmdt@crossref.orgMDT DepositInternational Journal of Circuits, Systems and Signal Processing1998-446410.46300/9106http://www.naun.org/cms.action?id=30293320233320231710.46300/9106.2023.17https://npublications.com/journals/circuitssystemssignal/2023.phpShermilaWeerasekaraFaculty of Information Technology, University of Moratuwa Katubedda, Moratuwa Sri LankaSamindaPremarathneFaculty of Information Technology, University of Moratuwa Katubedda, Moratuwa Sri LankaK. L.JayaratneUniversity of Colombo School of Computing No. 35, Reid Avenue, Colombo 07, Sri LankaFisheries industry is a vital sector of Sri Lanka’s economy and each departing and arriving fishing vessel should have gone through ample security check by the harbor authorities. But with the COVID 19 pandemic and social distancing procedure, harbor authorities are facing difficulties detecting and recognizing fishing vessels by getting on the boats as usual. Also, currently harbors are using a paper-based system for recording the information on boat departures and arrivals. This leads to the inefficiency of harbor management process, delays in rescue missions and failures of security missions. To solve these problems, this paper introduces a Boat Recognition and Automated Harbor Management System (BRAHMS) which is based on YOLO v5 algorithm. In this research, a novel de-skewing method is discovered for the slanted license plate recognition process. The de-skewing process aims for three main approaches: auto de-skewing, manual de-skewing and a hybrid de-skewing which uses both auto and manual processes together.36202336202376829https://npublications.com/journals/circuitssystemssignal/2023/a182005-009(2023).pdf10.46300/9106.2023.17.9https://npublications.com/journals/circuitssystemssignal/2023/a182005-009(2023).pdfThe National Aquatic Resources Research and Development Agency (NARA), "Fisheries Industry Outlook", 2018 10.1155/2020/1520872Zhijian Huang, Bowen Sui, Jiayi Wen and Guohe Jiang, "An Intelligent Ship Image/Video Detection and Classification Method with Improved Regressive Deep Convolutional Neural Network", Hindawi Complexity, Volume 2020, Article ID 1520872, 2020. Okan Atalar, Burak Bartan, "Ship Classification using Image Dataset". 10.1109/ijcnn.2018.8489629Laroca, R., Severo, E., Zanlorensi, L.A., Oliveira, L.S., Gonçalves, G.R., Schwartz, W.R. and Menotti, D., 2018, July. A robust real-time automatic license plate recognition based on the YOLO detector. In 2018 international joint conference on neural networks (ijcnn) (pp. 1-10). IEEE. "Epoch in Machine Learning: A Simple Introduction (2021)", Jigsaw Academy, 2021. [Online]. Available: https://www.jigsawacademy.com/blogs/ai-ml/epoch-inmachine-learning. [Accessed: 06- Dec- 2021]. Visa, S., Ramsay, B., Ralescu, A.L. and Van Der Knaap, E., 2011. Confusion matrix-based feature selection. MAICS, 710(1), pp.120-127.