Work Sharing: Object Detection for Autonomous Vehicles

This work sharing is about the research results of object detection technology for autonomous vehicles. In this work, we first conducted an in-depth study of related algorithms and technologies for target detection, including deep learning-based convolutional neural networks (CNN) and target detection algorithms (YOLO, Faster R-CNN, SSD, etc.). Then, we optimized and improved the algorithm for the special needs of autonomous vehicles. By performing a series of transformations on the data set through understanding the data set, we improved the training effect and generalization ability of the model. For the actual application scenarios of autonomous vehicles, we considered the impact of different weather conditions, lighting changes and traffic environments, and improved the robustness and stability of object detection through model improvements.

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