Please use this identifier to cite or link to this item: http://148.72.244.84/xmlui/handle/xmlui/15810
Title: A Review of Vehicle Accident Detection and Notification Systems Based on Machine Learning Techniques
Keywords: VehiclesAccidents, Machine learning, Object detection, Surveillance camera, Convolutional Neural Network (CNN), Region-based (RCNN).
Issue Date: 1-Apr-2024
Publisher: university of Diyala
Abstract: The rabid growth of the vehicles accidents on our roads are increasing as well as the number of human lives lost and the costs of repairing damages due to these accidents in order to reduce the dangers associated with accidents. A lot of researchers and specialists turn to electronic systems based on machine learning, deep learning techniques algorithms or any other artificial intelligence methods to detect and generate an emergency signal can reduce the time gap between the accident happening and the arrival of medical help. The main purpose of this review article was to identify and collect all the studies that have been done previously to detect roads traffics based on using machine learning techniques particularly deep learning. This paper will present all the methods that have been used and the experimental results of these studies and the research gabs they contain. We are following a systematic search plan passed on selected the papers that have the most similar keyword to make sure that all paper are exactly matching this paper subject so we apply this plan by using Springer, Elsevier, Electrical and Electronics Engineers (IEEE) xplore ,Google scholar, Arxiv, Sciencedirect and Researchgate datasets.From the all previous mentioned datasets we found 37 papers only 26of these papers are corresponded with the review subject
URI: http://148.72.244.84/xmlui/handle/xmlui/15810
ISSN: 2958-4612
Appears in Collections:مجلة ديالى للعلوم الاكاديمية / Academic Science Journal (Acad. Sci. J.)

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