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Apr, 2016
训练约束反卷积网络用于道路场景语义分割
Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation
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German Ros, Simon Stent, Pablo F. Alcantarilla, Tomoki Watanabe
TL;DR
该研究使用去卷积神经网络解决道路场景语义分割问题,提出了一个多域道路场景数据集,并通过新的训练策略实现对内存受限的目标网络(T-Net)的知识传递,使其在使用不到1%的内存的情况下实现比FCN更好的准确性。
Abstract
In this work we investigate the problem of
road scene
semantic segmentation
using
deconvolutional networks
(DNs). Several constraints limi
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