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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
Area Expedition Conference
Notes Approved no
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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Notes Approved no
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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Notes Approved no
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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Notes Approved no
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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Notes Approved no
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 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 (up) Hamburg, Germany Editor
Language English Summary Language English Original Title
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Area Expedition Conference 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Notes Approved no
Call Number cidis @ cidis @ Serial 41
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Author A. Amato; F. Lumbreras; Angel D. Sappa
Title A general-purpose crowdsourcing platform for mobile devices Type Conference Article
Year 2014 Publication Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 Abbreviated Journal
Volume 3 Issue Pages 211-215
Keywords Crowdsourcing Platform, Mobile Crowdsourcing
Abstract This paper presents details of a general purpose micro-taskon-demand platform based on the crowdsourcing philosophy. This platformwas specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquityand iii) embedded sensors.The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks.Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and task- solver).Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way.Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications.Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform.
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Publisher IEEE Place of Publication (up) Lisbon, Portugal Editor
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Area Expedition Conference Computer Vision Theory and Applications (VISAPP), 2014 International Conference on
Notes Approved no
Call Number cidis @ cidis @ Serial 25
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Author Cristhian A. Aguilera; Angel D. Sappa; R. Toledo
Title LGHD: A feature descriptor for matching across non-linear intensity variations Type Conference Article
Year 2015 Publication IEEE International Conference on, Quebec City, QC, 2015 Abbreviated Journal
Volume Issue Pages 178 - 181
Keywords Feature descriptor, multi-modal, multispectral, NIR, LWIR
Abstract This paper presents a new feature descriptor suitable to the task of matching features points between images with nonlinear intensity variations. This includes image pairs with significant illuminations changes, multi-modal image pairs and multi-spectral image pairs. The proposed method describes the neighbourhood of feature points combining frequency and spatial information using multi-scale and multi-oriented Log- Gabor filters. Experimental results show the validity of the proposed approach and also the improvements with respect to the state of the art.
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Publisher IEEE Place of Publication (up) Quebec City, QC, Canada Editor
Language English Summary Language English Original Title
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Area Expedition Conference 2015 IEEE International Conference on Image Processing (ICIP)
Notes Approved no
Call Number cidis @ cidis @ Serial 40
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