Multimodal Deep Learning in Semantic Image Segmentation-Reference-Cited by-同舟云学术

Multimodal Deep Learning in Semantic Image Segmentation

Published:2018 Issue: Volume: Page:
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Container-title:Proceedings of the 2018 International Conference on Cloud Computing and Internet of Things - CCIOT 2018
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Author:

Raman Vishal¹,Kumari Madhu¹

Affiliation:

1. NIT Hamirpur, Hamirpur, Himachal Pradesh, India

Publisher

ACM Press

Reference27 articles.

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2. S. R. Ahmed, J. P. Li, M. M. Hammad, and K. Asif. Image segmentation approach in multimodal information retrieval. In 2013--10th International Computer Conference on Wavelet Active Media Technology and Information Processing (IC-CWAMTIP), pages 167--170, Dec 2013.

3. T. Baltrusaitis, C. Ahuja, and L. Morency. Multimodal machine learning: A survey and taxonomy. CoRR, abs/1705.09406, 2017.

4. Y. Bengio, A. C. Courville, and P. Vincent. Unsupervised feature learning and deep learning: A review and new perspectives. CoRR, abs/1206.5538, 2012.

5. A. D. Costea and S. Nedevschi. Traffic scene segmentation based on boosting over multimodal low, intermediate and high order multi-range channel features. In Intelligent Vehi-cles Symposium (IV), 2017 IEEE, pages 74--81. IEEE, 2017.

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