Abstract
Machine intensive and cyclical earth-moving activities could benefit from genuine surveillance heavy machinery. It could provide accurate information for development purposes in the future. Reasonably clear sightlines and recognized machined, ground, earth-moving work locations are among the greatest choices for vision-based solutions. The server-customer interaction tracker (SCIT) seems to be a system that recognizes and monitors the unclean loading cycle by combining many cutting-edge image processing algorithms using spatiotemporal data and depth of understanding. For the SCIT technology, a proposed hybrid detection method is designed to monitor vehicles in optically cluttered entrance ramps. Video capturing underneath various settings is used to assess the built system. The SCIT device including its newly designed monitoring algorithm performed admirably, as evidenced by the incredible precision of the computer and ground truth statistical correlation.
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Rama Santosh Naidu, P., Satheesh, P., Srinivas, B., Sunkari, V. (2022). A Novel Hybrid Tracking Algorithm for Client–Server Connection Using a Machine Learning Technique. In: Satyanarayana, C., Gao, XZ., Ting, CY., Muppalaneni, N.B. (eds) Proceedings of the International Conference on Computer Vision, High Performance Computing, Smart Devices and Networks. Advanced Technologies and Societal Change. Springer, Singapore. https://doi.org/10.1007/978-981-19-4044-6_12
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DOI: https://doi.org/10.1007/978-981-19-4044-6_12
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