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Evaluation Timeline Prizes NeurIPS 2019 Self-driving technology presents a rare opportunity to improve the quality of life in many of our communities. Avoidable collisions, single-occupant commuters, and vehicle emissions are choking cities, while infrastructure strains under rapid urban growth.

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khanhvy31/3DObject_Detection_DatafromLyft

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Object_Detection_DatafromLyft

Evaluation Timeline Prizes NeurIPS 2019 Self-driving technology presents a rare opportunity to improve the quality of life in many of our communities. Avoidable collisions, single-occupant commuters, and vehicle emissions are choking cities, while infrastructure strains under rapid urban growth.

Model use: YOLO3 (Thanks to this tutorial: https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras) and LyftDataset: https://github.com/lyft/nuscenes-devkit/tree/master/lyft_dataset_sdk

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Evaluation Timeline Prizes NeurIPS 2019 Self-driving technology presents a rare opportunity to improve the quality of life in many of our communities. Avoidable collisions, single-occupant commuters, and vehicle emissions are choking cities, while infrastructure strains under rapid urban growth.

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