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Author Spencer Low, Oliver Nina, Angel D. Sappa, Erik Blasch, Nathan Inkawhich pdf  isbn
openurl 
  Title (up) 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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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 211  
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Author Spencer Low, Oliver Nina, Angel D. Sappa, Erik Blasch, Nathan Inkawhich pdf  isbn
openurl 
  Title (up) 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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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 212  
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Author Xavier Soria; Angel D. Sappa; Arash Akbarinia pdf  openurl
  Title (up) Multispectral Single-Sensor RGB-NIR Imaging: New Challenges an Oppotunities Type Conference Article
  Year 2017 Publication The 7th International Conference on Image Processing Theory, Tools and Application Abbreviated Journal  
  Volume Issue Pages 1-6  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 72  
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud pdf  openurl
  Title (up) Near InfraRed Imagery Colorization Type Conference Article
  Year 2018 Publication 25 th IEEE International Conference on Image Processing, ICIP 2018 Abbreviated Journal  
  Volume Issue Pages 2237-2241  
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  Abstract This paper proposes a stacked conditional Generative

Adversarial Network-based method for Near InfraRed

(NIR) imagery colorization. We propose a variant architecture

of Generative Adversarial Network (GAN) that uses multiple

loss functions over a conditional probabilistic generative model.

We show that this new architecture/loss-function yields better

generalization and representation of the generated colored IR

images. The proposed approach is evaluated on a large test

dataset and compared to recent state of the art methods using

standard metrics.1

Index Terms—Convolutional Neural Networks (CNN), Generative

Adversarial Network (GAN), Infrared Imagery colorization.
 
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 81  
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Author Rafael E. Rivadeneira, Henry O. Velesaca, Angel D. Sappa openurl 
  Title (up) 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 Henry O. Velesaca, Steven Araujo, Patricia L. Suarez, Ángel Sanchez & Angel D. Sappa pdf  isbn
openurl 
  Title (up) Off-the-Shelf Based System for Urban Environment Video Analytics. Type Conference Article
  Year 2020 Publication The 27th International Conference on Systems, Signals and Image Processing (IWSSIP 2020) Abbreviated Journal  
  Volume 2020-July Issue 9145121 Pages 459-464  
  Keywords Greenhouse gases, carbon footprint, object detection, object tracking, website framework, off-the-shelf video analytics.  
  Abstract This paper presents the design and implementation details of a system build-up by using off-the-shelf algorithms for urban video analytics. The system allows the connection to public video surveillance camera networks to obtain the necessary

information to generate statistics from urban scenarios (e.g., amount of vehicles, type of cars, direction, numbers of persons, etc.). The obtained information could be used not only for traffic management but also to estimate the carbon footprint of urban scenarios. As a case study, a university campus is selected to

evaluate the performance of the proposed system. The system is implemented in a modular way so that it is being used as a testbed to evaluate different algorithms. Implementation results are provided showing the validity and utility of the proposed approach.
 
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  ISSN 21578672 ISBN 978-172817539-3 Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 125  
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Author P. Ricaurte; C. Chilán; C. A. Aguilera-Carrasco; B. X. Vintimilla; Angel D. Sappa pdf  url
openurl 
  Title (up) Performance Evaluation of Feature Point Descriptors in the Infrared Domain Type Conference Article
  Year 2014 Publication Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2013 Abbreviated Journal  
  Volume 1 Issue Pages 545 -550  
  Keywords Infrared Imaging, Feature Point Descriptors  
  Abstract This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered.  
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  Publisher IEEE Place of Publication Editor  
  Language English Summary Language English Original Title  
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  Area Expedition Conference 2014 International Conference on Computer Vision Theory and Applications (VISAPP)  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 26  
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Author Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa pdf  openurl
  Title (up) PETRA: A Crowdsourcing-Based Platform for Rocks Data Collection and Characterization Type Conference Article
  Year 2019 Publication IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador Abbreviated Journal  
  Volume Issue Pages 1-6  
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  Abstract This paper presents details of a distributed platform intended for data acquisition, evaluation, storage and visualization, which is fully implemented under the crowdsourcing paradigm. The proposed platform is the result from collaboration between computer science and petrology researchers and it is intended for academic purposes. The platform is designed within a MTV (Model, Template and View) architecture and also designed for a collaborative data store and managing of rocks from multiple readers and writers, taking advantage of ubiquity of web applications, and neutrality of researchers from different

communities to validate the data. The platform is being used and validated by students and academics from our university; in the near future it will be open to other users interested on this topic.
 
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  Call Number gtsi @ user @ Serial 112  
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Author Cristhian A. Aguilera; Xaver Soria; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title (up) RGBN Multispectral Images: a Novel Color Restoration Approach Type Conference Article
  Year 2017 Publication 15th International Conference on Practical Applications of Agents and Multi-Agent Systems Abbreviated Journal  
  Volume 619 Issue Pages 155-163  
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  Call Number cidis @ cidis @ Serial 59  
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Author Angel Morera; Angel Sánchez; Angel D. Sappa; José F. Vélez pdf  openurl
  Title (up) Robust Detection of Outdoor Urban Advertising Panels in Static Images. Type Conference Article
  Year 2019 Publication 17th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2019); Ávila, España. Communications in Computer and Information Science Abbreviated Journal  
  Volume 1047 Issue Pages 246-256  
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  Abstract One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising

panels. For such a purpose, a previous stage is to accurately detect and

locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based

on a deep neural network architecture that minimizes the number of

false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection

over Union (IoU) accuracy metric make this proposal applicable in real

complex urban images.
 
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 107  
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