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Object Detection In Rural Roads Through Ssd and Yolo Framework
The objective of this work is the detection of objects in rural areas, this pa-per presents the use of deep learning frameworks used as You Only Look Once (YOLO) and another that belongs to the same category of one-stage is the well-known Single Shot Multi-Box Detector (SSD), in the state of the literature, produces excellent results in detecting objects in real-time. Our interest is in the detection of objects on rural roads, for this reason, we use images of rural roads with different environments to achieve an optimal balance between precision and precision in the detection of objects. Fur-thermore, as there is no dataset in these environments, we created our own data set to perform the experiments due to the difficulty of this problem. The result of both detectors has produced acceptable results under certain conditions like lighting conditions, viewing perspectives, partial occlusion of the object.