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Author Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa url  doi
openurl 
  Title Corn Kernel Classification From Few Training Samples Type Journal Article
  Year 2023 Publication In journal Artificial Intelligence in Agriculture Abbreviated Journal  
  Volume Vol. 9 Issue Pages pp. 89-99  
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  ISSN (down) 25897217 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 223  
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Author Armin Mehri; Parichehr Behjati; Angel Domingo Sappa pdf  openurl
  Title TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution. Type Journal Article
  Year 2023 Publication IEEE Access Abbreviated Journal  
  Volume Vol. 11 Issue Pages pp. 11529-11540  
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  ISSN (down) 21693536 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 207  
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Author Armin Mehri, Parichehr Behjati, Dario Carpio, and Angel D. Sappa pdf  openurl
  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 (down) 21693536 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 227  
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Author Abel Rubio, Wilton Agila, Leandro González & Jonathan Aviles-Cedeno pdf  openurl
  Title Distributed Intelligence in Autonomous PEM Fuel Cell Control. Type Journal Article
  Year 2023 Publication Energies 2023 Abbreviated Journal  
  Volume Vol. 16 Issue Issue 12 Pages  
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  ISSN (down) 19961073 ISBN Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 217  
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Author Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa pdf  openurl
  Title Fast CNN Stereo Depth Estimation through Embedded GPU Devices Type Journal Article
  Year 2020 Publication Sensors 2020 Abbreviated Journal  
  Volume Vol. 2020-June Issue 11 Pages pp. 1-13  
  Keywords stereo matching; deep learning; embedded GPU  
  Abstract Current CNN-based stereo depth estimation models can barely run under real-time

constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art

evaluations usually do not consider model optimization techniques, being that it is unknown what is

the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models

on three different embedded GPU devices, with and without optimization methods, presenting

performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth

estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture

for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically

augmenting the runtime speed of current models. In our experiments, we achieve real-time inference

speed, in the range of 5–32 ms, for 1216  368 input stereo images on the Jetson TX2, Jetson Xavier,

and Jetson Nano embedded devices.
 
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  Language English Summary Language English Original Title  
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  Series Volume Series Issue Edition  
  ISSN (down) 14248220 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 132  
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Author Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia url  doi
openurl 
  Title Dense extreme inception network for edge detection. Type Journal Article
  Year 2023 Publication Pattern Recognition Abbreviated Journal  
  Volume Vol. 139 Issue Pages  
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  Series Volume Series Issue Edition  
  ISSN (down) 00313203 ISBN Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 216  
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Author Cristhian A. Aguilera; Cristhian Aguilera; Angel D. Sappa pdf  openurl
  Title Melamine faced panels defect classification beyond the visible spectrum. Type Journal Article
  Year 2018 Publication In Sensors 2018 Abbreviated Journal  
  Volume Vol. 11 Issue Issue 11 Pages  
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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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  Notes Approved no  
  Call Number gtsi @ user @ Serial 89  
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Author Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa pdf  openurl
  Title Fine-tuning deep convolutional networks for lepidopterous genus recognition Type Journal Article
  Year 2017 Publication Lecture Notes in Computer Science Abbreviated Journal  
  Volume Vol. 10125 LNCS Issue Pages pp. 467-475  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 63  
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Author Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title Cross-Spectral Local Descriptors via Quadruplet Network Type Journal Article
  Year 2017 Publication In Sensors Journal Abbreviated Journal  
  Volume Vol. 17 Issue Pages pp. 873  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 64  
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Author Victor Santos; Angel D. Sappa; Miguel Oliveira pdf  openurl
  Title Special Issue on Autonomous Driving an Driver Assistance Systems Type Journal Article
  Year 2017 Publication In Robotics and Autonomous Systems Journal Abbreviated Journal  
  Volume Vol. 91 Issue Pages pp. 208-209  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 65  
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