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Neural Computing and Applications

Erschienen in:

11.09.2019 | Deep Learning & Neural Computing for Intelligent Sensing and Control

RETRACTED ARTICLE: Image object detection and semantic segmentation based on convolutional neural network

verfasst von: Laigang Zhang, Zhou Sheng, Yibin Li, Qun Sun, Ying Zhao, Deying Feng

Erschienen in: Neural Computing and Applications | Ausgabe 7/2020

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Abstract

In this paper, an unsupervised co-segmentation algorithm is proposed, which can be applied to the image with multiple foreground objects simultaneously and the background changes dramatically. The color edge image in RGB space is extracted for semantic extraction. This method can effectively distinguish foreground and background by recursively modeling the appearance distribution of pixels and regions. The coherence of image foreground and background model is enhanced by using the correlation between different image regions and image interior. Experimental results show that deep convolutional neural network can effectively realize semantic classification of scene images by end-to-end feature learning and achieve accurate semantic segmentation of scene images.

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Titel: RETRACTED ARTICLE: Image object detection and semantic segmentation based on convolutional neural network
verfasst von: Laigang Zhang
Zhou Sheng
Yibin Li
Qun Sun
Ying Zhao
Deying Feng
Publikationsdatum: 11.09.2019
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-019-04491-4

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