Posted by: xpertnest Category: AI & ML, Success Stories Comments: 0 Post Date: March 24, 2020 xpertnest2020-03-24T04:42:27+00:00 Challenges A US-based company needed to identify in real time road hazards such as vehicles, pedestrians, strollers, traffic lights, and traffic signs.Identified objects needed to be fed to another system where a driverless vehicle could take action.To ensure accurate detection and classification, the system needed to be trained for multiple iterations and fine-tuned. Xpertnest’s Solutions Xpertnest trained deep learning models to detect and classify different objects.Used YOLO V2 architecture, Darknet19, and custom Network in Network (NiN) architecture for object detection and classification.Integrated a lane detection algorithm into the system. Value Delivered The YOLO (You Only Look Once) architecture enabled the algorithm to scan a frame once to detect multiple objects, increasing speed.Enabled safe and reliable driverless navigation.The client saved time and was able to raise the quality of its candidates. Author xpertnest Leave a Reply Cancel replyYour email address will not be published. Required fields are marked *Comment * Name * Email * Website Save my name, email, and website in this browser for the next time I comment.
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