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Author (down) Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X. url  openurl
  Title Thermal Image Super-Resolution: A Novel Unsupervised Approach. Type Book Chapter
  Year 2022 Publication Communications in Computer and Information Science, 15th International Communications in Computer and Information Science Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Abbreviated Journal BOOK  
  Volume 1474 CCIS Issue Pages pp 495 – 506  
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  Call Number cidis @ cidis @ Serial 179  
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Author (down) Rivadeneira R.E., Sappa A.D., Vintimilla B.X., Nathan S., Kansal P., Mehri A et al. pdf  openurl
  Title Thermal Image Super-Resolution Challenge – PBVS 2021. Type Conference Article
  Year 2021 Publication In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021., junio 19 – 25, 2021 Abbreviated Journal  
  Volume Issue Pages 4354-4362  
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  Call Number cidis @ cidis @ Serial 151  
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Author (down) Rivadeneira R. E., Sappa A. D., Vintimilla B. X. and Hammoud R. url  openurl
  Title A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. Type Journal Article
  Year 2022 Publication In Sensors. Abbreviated Journal In Sensors  
  Volume Vol. 22 Issue Issue 6 Pages Article number 2254  
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  Call Number cidis @ cidis @ Serial 170  
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Author (down) Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa pdf  url
openurl 
  Title Feature Point Descriptors: Infrared and Visible Spectra Type Journal Article
  Year 2014 Publication Sensors Journal Abbreviated Journal  
  Volume 14 Issue Pages 3690-3701  
  Keywords 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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Author (down) Ricardo Cajo; Wilton Agila pdf  url
openurl 
  Title Evaluation of algorithms for linear and nonlinear PID control for Twin Rotor MIMO System Type Conference Article
  Year 2015 Publication Computer Aided System Engineering (APCASE), 2015 Asia-Pacific Conference on, Quito, 2015 Abbreviated Journal  
  Volume Issue Pages 214-219  
  Keywords Twin Rotor MIMO System (TRMS); Proportional-Integral-Derivative (PID); Linear PID Controller; Nonlinear PID Controller; Nonlinear Observer  
  Abstract In this paper the linear and nonlinear PID control algorithms are analyzed and for a twin rotor MIMO system (TRMS), whose characteristic is not linear with two degrees of freedom and cross-links. The aim of this work is to stabilize the TRMS, to achieve a particular position and follow a trajectory in the shortest time. Mathematical modeling of helicopter model is simulated using MATLAB / Simulink, the two degrees of freedom are controlled both horizontally and vertically through the proposed controllers. Also nonlinear segmented observers for each degree of freedom are designed in order to measure statements required by the nonlinear controller. Followed, a comparative analysis of both algorithms is presented to evaluate their performance in the real TRMS.  
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  Publisher IEEE Place of Publication Editor  
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  Area Expedition Conference 2015 Asia-Pacific Conference on Computer Aided System Engineering  
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  Call Number cidis @ cidis @ Serial 36  
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Author (down) Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa pdf  openurl
  Title 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  
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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 (down) Rangnekar,Aneesha; Mulhollan,Zachary; Vodacek,Anthony; Hoffman,Matthew; Sappa,Angel D.; Yu,Jun et al. pdf  openurl
  Title Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. Type Conference Article
  Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE  
  Volume 2022-June Issue Pages 389 - 397  
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  Call Number cidis @ cidis @ Serial 176  
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Author (down) Rafael E. Rivadeneira; Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla. pdf  openurl
  Title Thermal Image SuperResolution through Deep Convolutional Neural Network. Type Conference Article
  Year 2019 Publication 16th International Conference on Image Analysis and Recognition (ICIAR 2019); Waterloo, Canadá Abbreviated Journal  
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  Abstract Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a superesolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process a new thermal images dataset is used. Di?erent experiments have been carried out, ?rstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www.cidis.espol.edu.ec/es/dataset  
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  Call Number gtsi @ user @ Serial 103  
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Author (down) Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla; Lin Guo; Jiankun Hou; Armin Mehri; Parichehr Behjati; Ardakani Heena Patel; Vishal Chudasama; Kalpesh Prajapati; Kishor P. Upla; Raghavendra Ramachandra; Kiran Raja; Christoph Busch; Feras Almasri; Olivier Debeir; Sabari Nathan; Priya Kansal; Nolan Gutierrez; Bardia Mojra; William J. Beksi pdf  isbn
openurl 
  Title Thermal Image Super-Resolution Challenge – PBVS 2020 Type Conference Article
  Year 2020 Publication The 16th IEEE Workshop on Perception Beyond the Visible Spectrum on the Conference on Computer Vision and Pattern Recongnition (CVPR 2020) Abbreviated Journal  
  Volume 2020-June Issue 9151059 Pages 432-439  
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  Abstract This paper summarizes the top contributions to the first challenge on thermal image super-resolution (TISR) which was organized as part of the Perception Beyond the Visible Spectrum (PBVS) 2020 workshop. In this challenge, a novel thermal image dataset is considered together with stateof-the-art approaches evaluated under a common framework.

The dataset used in the challenge consists of 1021 thermal images, obtained from three distinct thermal cameras at different resolutions (low-resolution, mid-resolution, and high-resolution), resulting in a total of 3063 thermal images. From each resolution, 951 images are used for training and 50 for testing while the 20 remaining images are used for two proposed evaluations. The first evaluation consists of downsampling the low-resolution, midresolution, and high-resolution thermal images by x2, x3 and x4 respectively, and comparing their super-resolution

results with the corresponding ground truth images. The second evaluation is comprised of obtaining the x2 superresolution from a given mid-resolution thermal image and comparing it with the corresponding semi-registered highresolution thermal image. Out of 51 registered participants, 6 teams reached the final validation phase.
 
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  ISSN 21607508 ISBN 978-172819360-1 Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 123  
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Author (down) Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla pdf  isbn
openurl 
  Title Thermal Image Super-Resolution: a Novel Architecture and Dataset Type Conference Article
  Year 2020 Publication The 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020); Valletta, Malta; 27-29 Febrero 2020 Abbreviated Journal  
  Volume 4 Issue Pages 111-119  
  Keywords Thermal images, Far Infrared, Dataset, Super-Resolution.  
  Abstract This paper proposes a novel CycleGAN architecture for thermal image super-resolution, together with a large

dataset consisting of thermal images at different resolutions. The dataset has been acquired using three thermal

cameras at different resolutions, which acquire images from the same scenario at the same time. The thermal

cameras are mounted in rig trying to minimize the baseline distance to make easier the registration problem.

The proposed architecture is based on ResNet6 as a Generator and PatchGAN as Discriminator. The novelty

on the proposed unsupervised super-resolution training (CycleGAN) is possible due to the existence of aforementioned thermal images—images of the same scenario with different resolutions. The proposed approach

is evaluated in the dataset and compared with classical bicubic interpolation. The dataset and the network are

available.
 
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  Series Volume Series Issue Edition  
  ISSN ISBN 978-989758402-2 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 121  
Permanent link to this record
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