Tinier-YOLO: A Real-Time Object Detection Method for Constrained Environments

@article{Fang2020TinierYOLOAR,
  title={Tinier-YOLO: A Real-Time Object Detection Method for Constrained Environments},
  author={Wei Fang and L. Wang and Peiming Ren},
  journal={IEEE Access},
  year={2020},
  volume={8},
  pages={1935-1944}
}
Deep neural networks (DNNs) have shown prominent performance in the field of object detection. However, DNNs usually run on powerful devices with high computational ability and sufficient memory, which have greatly limited their deployment for constrained environments such as embedded devices. YOLO is one of the state-of-the-art DNN-based object detection approaches with good performance both on speed and accuracy and Tiny-YOLO-V3 is its latest variant with a small model that can run on… Expand
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