Abstract
The goal of this research is to find out YOLO algorithm's effectiveness on detecting the number of vehicle on road. Our activity in this research is conduct training using a dataset that we created ourselves and do traffic recording simulation in a lot of scenario using YOLO original datasets and our own datasets. The result of this research is YOLO algorithm successfully detects vehicles as much as 65.3% of the total vehicles passing on the highway and gives the wrong label as much as 20.7% of the total label given if using YOLO original dataset. YOLO algorithm successfully detects vehicles as much as 9,3% of the total vehicles passing on the highway and gives the wrong label as much as 7,4% of the total label given if using our own dataset.
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Dewantoro, N., Fernando, P. N., & Tan, S. (2020). YOLO Algorithm Accuracy Analysis in Detecting Amount of Vehicles at the Intersection. In IOP Conference Series: Earth and Environmental Science (Vol. 426). Institute of Physics Publishing. https://doi.org/10.1088/1755-1315/426/1/012164
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