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Semantic segmentation and scene understanding with image color identification
Department of Electrical and Computer engineering, University of California, San Diego.
Research Article
International Journal of Science and Research Archive, 2021, 02(02), 313-316.
Article DOI: 10.30574/ijsra.2021.2.2.0006
Publication history:
Received on 10 March 2021; revised on 20 May 2021; accepted on 28 May 2021
Abstract:
Semantic segmentation and scene understanding are pivotal in computer vision, particularly for applications like autonomous driving, medical imaging, and robotics. This paper explores how incorporating image color identification can enhance the performance and accuracy of semantic segmentation models. Through a series of experiments, we evaluate the contribution of color-based features in deep learning architectures, illustrating improvements in both object recognition and scene context awareness.
Keywords:
Semantic segmentation; Machine learning; Deep learning; Image processing
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
