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Journal of Imaging, Volume 4, Issue 10

2018 October - 14 articles

Cover Story: This paper describes the idea of Encoder-decoder-based CNN for Road-Scene Understanding named ECRU. The proposed model offers a simplified CNN architecture with less overhead and higher performance. It makes use of the special method of re-using pooling indices, which leads to fewer computation parameters and helps to reduce inference time. The proposed network model is well suited for scene understanding applications. It could be employed for driving assistance to offer enhanced vehicle safety and more generally road safety. The network is trained and tested on the famous road scenes dataset CamVid and offers outstanding outcomes in comparison to similar previously published methods. View this paper
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J. Imaging - ISSN 2313-433X
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