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Real-Time Lightweight CNN for Detecting Road Object of Various Size

机译:实时轻量级CNN用于检测各种尺寸的道路物体

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摘要

This paper proposed a novel lightweight convolutional neural network suitable for road object detection which not only for small objects, but for large objects. The proposed network outperformed detection performance of existing convolutional neural networks on KITTI datasets and satisfied real-time processing speed of 10ms on PC and 65ms on NVIDIA TX2. The model is suitable for running in an embedded environment with only 3-million weight parameters.
机译:本文提出了一种新颖的轻量级卷积神经网络,不仅适用于小物体,而且适用于大型物体,适用于道路物体检测。拟议的网络性能优于KITTI数据集上现有卷积神经网络的检测性能,并满足PC上10ms和NVIDIA TX2上65ms的实时处理速度。该模型适合在重量参数只有300万的嵌入式环境中运行。

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