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Author Angel D. Sappa. url  openurl
  Title ICT Applications for Smart Cities Type Book Chapter
  Year 2022 Publication (down) Intelligent Systems Reference Library Abbreviated Journal BOOK  
  Volume 224 Issue Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 198  
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Author M. Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel D. Sappa; A. Tomé pdf  url
openurl 
  Title Concurrent Learning of Visual Codebooks and Object Categories in Open- ended Domains Type Conference Article
  Year 2015 Publication (down) Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, Hamburg, Germany, 2015 Abbreviated Journal  
  Volume Issue Pages 2488 - 2495  
  Keywords Birds, Training, Legged locomotion, Visualization, Histograms, Object recognition, Gaussian mixture model  
  Abstract In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are usually constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using codebooks constructed offline.  
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  Publisher IEEE Place of Publication Hamburg, Germany Editor  
  Language English Summary Language English Original Title  
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  Area Expedition Conference 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 41  
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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 (down) 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 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 (down) 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 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 (down) 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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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 (down) In Robotics and Autonomous Systems Abbreviated Journal  
  Volume 121 Issue Pages  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 119  
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Author Rubio, G.A., Agila, W.E pdf  openurl
  Title A fuzzy model to manage water in polymer electrolyte membrane fuel cells Type Journal Article
  Year 2021 Publication (down) In Processes Journal. (Article number 904) Abbreviated Journal  
  Volume Vol. 9 Issue Issue 6 Pages  
  Keywords PEM fuel cell, fuzzy, neural network, electrical response, flooding, drying.  
  Abstract In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response and consequently, its autonomous operation. By applying load, current and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 mV to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 mV to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits.  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 153  
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Author Santos, V., Sappa, A.D., Oliveira, M. & de la Escalera, A. pdf  openurl
  Title Editorial: Special Issue on Autonomous Driving and Driver Assistance Systems – Some Main Trends Type Journal Article
  Year 2021 Publication (down) In Journal: Robotics and Autonomous Systems. (Article number 103832) Abbreviated Journal  
  Volume Vol. 144 Issue Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 158  
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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 (down) In journal Artificial Intelligence in Agriculture Abbreviated Journal  
  Volume Vol. 9 Issue Pages pp. 89-99  
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  ISSN 25897217 ISBN Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 223  
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Author Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. pdf  openurl
  Title Camera pose estimation in multi-view environments:from virtual scenarios to the real world Type Journal Article
  Year 2021 Publication (down) In Image and Vision Computing Journal. (Article number 104182) Abbreviated Journal  
  Volume Vol. 110 Issue Pages  
  Keywords Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments  
  Abstract This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired

images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of

overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly

trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the

relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity

on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the

scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used,

highlighting the importance on the similarity between virtual-real scenarios.
 
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 147  
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