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Viñán-Ludeña, M.S., Roberto Jacome Galarza, Montoya, L.R., Leon, A.V., & Ramírez, C.C. |
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Smart university: an architecture proposal for information management using open data for research projects. |
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Journal Article |
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2020 |
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Advances in Intelligent Systems and Computing |
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1137 AISC, 2020 |
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172-178 |
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no |
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Call Number |
cidis @ cidis @ |
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188 |
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Author |
Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. |
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Title |
LDC: Lightweight Dense CNN for Edge Detection. |
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2022 |
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IEEE Access journal |
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Vol. 10 |
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pp. 68281-68290 |
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yes |
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cidis @ cidis @ |
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183 |
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Author |
Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia |
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Journal Article |
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2023 |
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Dense extreme inception network for edge detection. Pattern Recognition |
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Vol. 139 |
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cidis @ cidis @ |
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216 |
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Author |
Xavier Soria; Angel D. Sappa; Riad Hammoud |
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Title |
Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Image. Sensors 2018 ,2059. |
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Journal Article |
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2018 |
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Vol. 18 |
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Issue 7 |
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Abstract |
Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700–1100 nm) cross-talking with the visible bands (400–700 nm). This paper proposes two deep learning-based architectures to recover the full RGB color images, thus removing the NIR information from the visible bands. The proposed approaches directly restore the high-resolution RGB image by means of convolutional neural networks. They are evaluated with several outdoor images; both architectures reach a similar performance when evaluated in different scenarios and using different similarity metrics. Both of them improve the state of the art approaches. |
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gtsi @ user @ |
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96 |
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