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OUTCOME: The survey says MobileNets has higher accuracy when compared to VGG16, VGG19 and Inception V3 and is therefore chosen to be used with SSD. The impact of the differences in the amount of training of each algorithm is highlighted which helps understand the advantages and disadvantages of each algorithm and deduce the most suitable.<\/jats:p>","DOI":"10.3233\/kes-220002","type":"journal-article","created":{"date-parts":[[2022,6,17]],"date-time":"2022-06-17T16:13:39Z","timestamp":1655482419000},"page":"7-16","source":"Crossref","is-referenced-by-count":35,"title":["Analysis of deep learning frameworks for object detection in motion"],"prefix":"10.1177","volume":"26","author":[{"given":"Vaishnavi","family":"Gururaj","sequence":"first","affiliation":[]},{"given":"Shriya\u00a0Varada","family":"Ramesh","sequence":"additional","affiliation":[]},{"given":"Sanjana","family":"Satheesh","sequence":"additional","affiliation":[]},{"given":"Ashwini","family":"Kodipalli","sequence":"additional","affiliation":[]},{"given":"Kusuma","family":"Thimmaraju","sequence":"additional","affiliation":[]}],"member":"179","reference":[{"issue":"3","key":"10.3233\/KES-220002_ref3","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1049\/iet-its.2011.0138","article-title":"Helmet presence classification with motorcycle detection and tracking","volume":"6","author":"Chiverton","year":"2012","journal-title":"IET Intelligent Transport Systems"},{"key":"10.3233\/KES-220002_ref4","doi-asserted-by":"publisher","first-page":"52","DOI":"10.5120\/ijca2019918770","article-title":"A review on helmet detection by using image processing and convolutional neural networks","volume":"182","author":"Prajwal","year":"2019","journal-title":"International Journal of Computer Applications"},{"key":"10.3233\/KES-220002_ref5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3233\/JIFS-191917","article-title":"A real-time traffic environmental perception algorithm fusing stereo vision and deep network","volume":"39","author":"Lian","year":"2020","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/KES-220002_ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s12065-020-00493-7"},{"key":"10.3233\/KES-220002_ref7","doi-asserted-by":"crossref","unstructured":"Vishnu C, Singh D, Mohan CK, Babu S. Detection of motorcyclists without helmet in videos using convolutional neural network. International Joint Conference on Neural Networks (IJCNN); Anchorage, AK. 2017; 3036-3041.","DOI":"10.1109\/IJCNN.2017.7966233"},{"issue":"4","key":"10.3233\/KES-220002_ref8","first-page":"1029","article-title":"Object detection and recognition in images","volume":"5","author":"Kumar","year":"2017","journal-title":"International Journal of Engineering Development and Research"},{"key":"10.3233\/KES-220002_ref9","doi-asserted-by":"crossref","unstructured":"Li K, Zhao X, Bian J, Tan M. Automatic safety helmet wearing detection. IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER); Honolulu, HI. 2017; 617-622.","DOI":"10.1109\/CYBER.2017.8446080"},{"key":"10.3233\/KES-220002_ref10","unstructured":"Baruah A, Kandali AB. Pedestrian detection on openCV and tensorFlow. Int. 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