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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 (down) pp 68281 – 68290  
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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 183  
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Author Armin Mehri; Parichehr Behjati; Angel Domingo Sappa url  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 (down) pp. 11529 - 11540  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 207  
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Author 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 (down) 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 Rafael E. Rivadeneira, Angel Domingo Sappa, 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 (down) Article number 2254  
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  Call Number cidis @ cidis @ Serial 170  
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Author Morocho-Cayamcela, M.E. & W. Lim pdf  openurl
  Title Lateral confinement of high-impedance surface-waves through reinforcement learning Type Journal Article
  Year 2020 Publication Electronics Letters Abbreviated Journal  
  Volume 56 Issue 23, 12 November 2020 Pages (down) 1262-1264  
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  Abstract The authors present a model-free policy-based reinforcement learning

model that introduces perturbations on the pattern of a metasurface.

The objective is to learn a policy that changes the size of the

patches, and therefore the impedance in the sides of an artificially structured

material. The proposed iterative model assigns the highest reward

when the patch sizes allow the transmission along a constrained path

and penalties when the patch sizes make the surface wave radiate to

the sides of the metamaterial. After convergence, the proposed

model learns an optimal patch pattern that achieves lateral confinement

along the metasurface. Simulation results show that the proposed

learned-pattern can effectively guide the electromagnetic wave

through a metasurface, maintaining its instantaneous eigenstate when

the homogeneity is perturbed. Moreover, the pattern learned to

prevent reflections by changing the patch sizes adiabatically. The

reflection coefficient S1, 2 shows that most of the power gets transferred

from the source to the destination with the proposed design.
 
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  Call Number cidis @ cidis @ Serial 139  
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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 (down) 873  
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  Call Number gtsi @ user @ Serial 64  
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Author Rosero Vasquez Shendry url  openurl
  Title Facial recognition: traditional methods vs. methods based on deep learning. Advances in Intelligent Systems and Computing – Information Technology and Systems Proceedings of ICITS 2020. Type Journal Article
  Year 2020 Publication Abbreviated Journal  
  Volume Issue Pages (down) 615-625  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 145  
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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 (down) pp 497 – 507  
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  Call Number cidis @ cidis @ Serial 184  
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Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic pdf  openurl
  Title Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles Type Journal Article
  Year 2016 Publication Journal of Automation and Control Engineering (JOACE) Abbreviated Journal  
  Volume 4 Issue Pages (down) 430-436  
  Keywords Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System  
  Abstract Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset.  
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  Call Number cidis @ cidis @ Serial 51  
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Author Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias; A. Paulo Moreira pdf  url
openurl 
  Title Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives Type Journal Article
  Year 2016 Publication Robotics and Autonomous Systems Journal Abbreviated Journal  
  Volume 83 Issue Pages (down) 312-325  
  Keywords Incremental scene reconstructionPoint cloudsAutonomous vehiclesPolygonal primitives  
  Abstract When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques.  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 49  
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