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Author Daniela Rato, Miguel Oliviera, Victor Santos, Manuel Gomes & Angel Sappa url  openurl
  Title A Sensor-to-Pattern Calibration Framework for Multi-Modal Industrial Collaborative Cells. Type Journal Article
  Year 2022 Publication Journal of Manufacturing Systems Abbreviated Journal  
  Volume Vol. 64 Issue Pages pp 497 – 507  
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  Call Number (up) cidis @ cidis @ Serial 184  
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Author Pereira J., Mora M. & W. Agila openurl 
  Title Qualitative Model to Maximize Shrimp Growth at Low Cost Type Journal Article
  Year 2021 Publication 5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 Abbreviated Journal  
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  Call Number (up) cidis @ cidis @ Serial 167  
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Author Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. url  openurl
  Title LDC: Lightweight Dense CNN for Edge Detection. Type Journal Article
  Year 2022 Publication IEEE Access journal Abbreviated Journal  
  Volume Vol. 10 Issue Pages pp 68281 – 68290  
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  Call Number (up) cidis @ cidis @ Serial 183  
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Author Ulises Gildardo Quiroz Antúnez, Alejandro Ismael Monterroso Rivas, María Fernanda Calderón Vega, Adán Guillermo Ramírez García openurl 
  Title APTITUDE OF COFFEE (COFFEA ARABICA L.) AND CACAO (THEOBROMA CACAO L.) CROPS CONSIDERING CLIMATE CHANGE Type Journal Article
  Year 2022 Publication Granja Abbreviated Journal  
  Volume 36 Issue 2 Pages  
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  Call Number (up) cidis @ cidis @ Serial 200  
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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  
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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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  Call Number (up) 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  
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  Call Number (up) 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 17 Issue Pages 873  
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  Call Number (up) gtsi @ user @ Serial 64  
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Author Victor Santos; Angel D. Sappa; Miguel Oliveira pdf  openurl
  Title Spcial Issue on Autonomous Driving an Driver Assistance Systems Type Journal Article
  Year 2017 Publication In Robotics and Autonomous Systems Journal Abbreviated Journal  
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  Call Number (up) gtsi @ user @ Serial 65  
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Author Xavier Soria; Angel D. Sappa; Riad Hammoud pdf  openurl
  Title Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Image. Sensors 2018, 18(7), 2059. Type Journal Article
  Year 2018 Publication Abbreviated Journal  
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  Abstract Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700–1100 nm) cross-talking with the visible bands (400–700 nm). This paper proposes two deep learning-based architectures to recover the full RGB color images, thus removing the NIR information from the visible bands. The proposed approaches directly restore the high-resolution RGB image by means of convolutional neural networks. They are evaluated with several outdoor images; both architectures reach a similar performance when evaluated in different scenarios and using different similarity metrics. Both of them improve the state of the art approaches.  
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  Call Number (up) gtsi @ user @ Serial 96  
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Author Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A. pdf  openurl
  Title Special Issue on Autonomous Driving and Driver Assistance Systems Type Journal Article
  Year 2019 Publication In Robotics and Autonomous Systems Abbreviated Journal  
  Volume Vol. 121 Issue Pages  
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  Notes Approved no  
  Call Number (up) gtsi @ user @ Serial 119  
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