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Author |
Patricia L. Suarez, Dario Carpio, Angel D. Sappa |
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Title |
Enhancement of Guided Thermal Image Super-Resolution Approaches |
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2024 |
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Neurocomputing |
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573 |
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Neurocomputing |
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cidis @ cidis @ |
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247 |
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Author |
Henry O. Velesaca, Gisel Bastidas, Mohammad Rouhani, Angel D. Sappa |
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Title |
Multimodal image registration techniques: a comprehensive survey |
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2024 |
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Multimedia Tools and Applications |
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Vol. 83 |
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63919 - 63947 |
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13807501 |
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cidis @ cidis @ |
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248 |
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Author |
Leo Ramos & Angel D. Sappa |
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Title |
Multispectral Semantic Segmentation for Land Cover Classification: An Overview |
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2024 |
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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Vol. 17 |
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14295-14336 |
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cidis @ cidis @ |
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250 |
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Author |
Cristhian A. Aguilera; Cristhian Aguilera; Angel D. Sappa |
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Title |
Melamine faced panels defect classification beyond the visible spectrum. |
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Journal Article |
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Year |
2018 |
Publication |
In Sensors 2018 |
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Vol. 11 |
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Issue 11 |
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Abstract |
In this work, we explore the use of images from different spectral bands to classify defects in melamine faced panels, which could appear through the production process. Through experimental evaluation, we evaluate the use of images from the visible (VS), near-infrared (NIR), and long wavelength infrared (LWIR), to classify the defects using a feature descriptor learning approach together with a support vector machine classifier. Two descriptors were evaluated, Extended Local Binary Patterns (E-LBP) and SURF using a Bag of Words (BoW) representation. The evaluation was carried on with an image set obtained during this work, which contained five different defect categories that currently occurs in the industry. Results show that using images from beyond
the visual spectrum helps to improve classification performance in contrast with a single visible spectrum solution. |
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gtsi @ user @ |
Serial |
89 |
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Author |
Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa |
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Title |
Fine-tuning deep convolutional networks for lepidopterous genus recognition |
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Journal Article |
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Year |
2017 |
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Lecture Notes in Computer Science |
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Vol. 10125 LNCS |
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pp. 467-475 |
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gtsi @ user @ |
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63 |
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Author |
Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo |
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Title |
Cross-Spectral Local Descriptors via Quadruplet Network |
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Journal Article |
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Year |
2017 |
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In Sensors Journal |
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Vol. 17 |
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pp. 873 |
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gtsi @ user @ |
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64 |
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Author |
Victor Santos; Angel D. Sappa; Miguel Oliveira |
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Title |
Special Issue on Autonomous Driving an Driver Assistance Systems |
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Journal Article |
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Year |
2017 |
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In Robotics and Autonomous Systems Journal |
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Vol. 91 |
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pp. 208-209 |
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gtsi @ user @ |
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65 |
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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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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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Author |
Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A. |
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Special Issue on Autonomous Driving and Driver Assistance Systems |
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Journal Article |
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2019 |
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In Robotics and Autonomous Systems |
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121 |
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gtsi @ user @ |
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119 |
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