Perceptual Quality Evaluation of Corrupted Industrial Images-Reference-Cited by-同舟云学术

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Perceptual Quality Evaluation of Corrupted Industrial Images

Published:2022 Issue: Volume: Page:191-202
ISSN:1865-0929
Container-title:Digital TV and Wireless Multimedia Communications
language:
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Author:

Gong Yafei,Peng Chenchen,Liu Jing,Zhou Chengxu,Liu Hongyan

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2266-4_15

Reference44 articles.

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2. Gu, K., Xia, Z., Qiao, J., Lin, W.: Deep dual-channel neural network for image-based smoke detection. IEEE Trans. Multimed. 22(2), 311–323 (2020)

3. Li, L., Wang, G., Cormack, L., Bovik, A.C.: Efficient and secure image communication system based on compressed sensing for IoT monitoring applications. IEEE Trans. Multimed. 22(1), 82–95 (2020)

4. de Araujo, P.R.M., Lins, R.G.: Computer vision system for workpiece referencing in three-axis machining centers. Int. J. Adv. Manuf. Technol. 106, 2007–2020 (2020)

5. Kessler, M., Siewerdsen, J., Sonke, J.: Tu-C (SAM)-BRC-01: multimodality image acquisition, processing and display for guiding and adapting radiation therapy. Med. Phys. 38(6), 3751 (2011)

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1. Multiple Levels Perceptual Noise Backed Visual Information Fidelity for Picture Quality Assessment;2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS);2022-11-22

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