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Author Angel D. Sappa.
Title ICT Applications for Smart Cities Type Book Chapter
Year 2022 Publication Intelligent Systems Reference Library Abbreviated Journal BOOK
Volume 224 Issue Pages
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Call Number cidis @ cidis @ Serial 198
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Author Spencer Low, Oliver Nina, Angel D. Sappa, Erik Blasch, Nathan Inkawhich
Title Multi-modal Aerial View Image Challenge: Translation from Synthetic Aperture Radar to Electro-Optical Domain Results – PBVS 2023 Type Conference Article
Year 2023 Publication 19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition CVPR 2023, junio 18-28 Abbreviated Journal
Volume 2023-June Issue Pages 515 - 523
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ISSN 21607508 ISBN 979-835030249-3 Medium
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Call Number cidis @ cidis @ Serial 211
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Author Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Chenyang Wang, Junjun Jiang, Xianming Liu, Zhiwei Zhong, Dai Bin, Li Ruodi, Li Shengye
Title Thermal Image Super-Resolution Challenge Results – PBVS 2023 Type Conference Article
Year 2023 Publication 19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition CVPR 2023, junio 18-28 Abbreviated Journal
Volume 2023-June Issue Pages 470 - 478
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ISSN 21607508 ISBN 979-835030249-3 Medium
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Call Number cidis @ cidis @ Serial 210
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Author Spencer Low, Oliver Nina, Angel D. Sappa, Erik Blasch, Nathan Inkawhich
Title Multi-modal Aerial View Object Classification Challenge Results – PBVS 2023 Type Conference Article
Year 2023 Publication 19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition CVPR 2023, junio 18-28 Abbreviated Journal
Volume 2023-June Issue Pages 412 - 421
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ISSN 21607508 ISBN 979-835030249-3 Medium
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Call Number cidis @ cidis @ Serial 212
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Author Gisel Bastidas-Guacho, Patricio Moreno-Vallejo, Boris Vintimilla, Angel D. Sappa
Title Application on the Loop of Multimodal Image Fusion: Trends on Deep-Learning Based Approaches Type Conference Article
Year 2023 Publication IEEE 13th International Conference on Pattern Recognition Systems ICPRS 2023, julio 4-7 Abbreviated Journal
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ISSN ISBN 979-835033337-4 Medium
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Call Number cidis @ cidis @ Serial 213
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Author Rafael E. Rivadeneira, Henry O. Velesaca, Angel D. Sappa
Title Object Detection in Very Low-Resolution Thermal Images through a Guided-Based Super-Resolution Approach Type Conference Article
Year 2023 Publication 17th International Conference On Signal Image Technology & Internet Based System Abbreviated Journal
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Call Number cidis @ cidis @ Serial 224
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Author Armin Mehri, Parichehr Behjati, Dario Carpio, and Angel D. Sappa
Title SRFormer: Efficient Yet Powerful Transformer Network For Single Image Super Resolution Type Journal Article
Year 2023 Publication IEEE access Abbreviated Journal
Volume Vol. 11 Issue Pages 121457 - 121469
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ISSN 21693536 ISBN Medium
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Call Number cidis @ cidis @ Serial 227
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Author Xavier Soria, Yachuan Li, Mohammad Rouhani & Angel D. Sappa
Title Tiny and Efficient Model for the Edge Detection Generalization Type Conference Article
Year 2023 Publication Proceedings – 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023 Abbreviated Journal
Volume Issue Pages 1356 - 1365
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Call Number cidis @ cidis @ Serial 229
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Author M. Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel D. Sappa; A. Tomé
Title Concurrent Learning of Visual Codebooks and Object Categories in Open- ended Domains Type Conference Article
Year 2015 Publication Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, Hamburg, Germany, 2015 Abbreviated Journal
Volume Issue Pages 2488 - 2495
Keywords (up) Birds, Training, Legged locomotion, Visualization, Histograms, Object recognition, Gaussian mixture model
Abstract In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are usually constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using codebooks constructed offline.
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Publisher IEEE Place of Publication Hamburg, Germany Editor
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Area Expedition Conference 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Call Number cidis @ cidis @ Serial 41
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Author Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa
Title Feature Point Descriptors: Infrared and Visible Spectra Type Journal Article
Year 2014 Publication Sensors Journal Abbreviated Journal
Volume Vol. 14 Issue Pages pp. 3690-3701
Keywords (up) cross-spectral imaging; feature point descriptors
Abstract This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.
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Call Number cidis @ cidis @ Serial 28
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