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Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Chenyang Wang, Junjun Jiang, Xianming Liu, Zhiwei Zhong, Dai Bin, Li Ruodi, Li Shengye |

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Title |
Thermal Image Super-Resolution Challenge Results – PBVS 2023 |
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Conference Article |
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Year |
2023 |
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19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition (CVPR 2023) Vancouver, 18-28 junio 2023 |
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2023-June |
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470 - 478 |
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21607508 |
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979-835030249-3 |
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cidis @ cidis @ |
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210 |
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Author |
Omar Coello, Moisés Coronel, Darío Carpio, Boris X. Vintimilla & Luis Chuquimarca |


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Title |
Enhancing Apple’s Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging |
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2024 |
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14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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cidis @ cidis @ |
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244 |
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Author |
Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin |


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Title |
Classifying Healthy and Defective Fruits with a Multi-Input Architecture and CNN Models |
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Conference Article |
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2024 |
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14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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cidis @ cidis @ |
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245 |
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Author |
Emmanuel F. Morán, Boris X. Vintimilla, Miguel A. Realpe |


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Title |
Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves |
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2024 |
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 26th Iberoamerican Congress on Pattern Recognition, CIARP 2023 Coimbra 27 – 30 November 2023 |
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Vol. 14470 |
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257–271 |
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03029743 |
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978-303149017-0 |
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cidis @ cidis @ |
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249 |
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Author |
Kevin E. Munoz, Loberlly N. Salazar, Steven S. Araujo, and Boris X. Vintimilla |
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Title |
Stereo Vision Techniques: A Comparative Study of Traditional and Machine Learning-Based Approaches |
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2025 |
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5th International Conference on Computer Vision and Robotics CVR 2025 |
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no |
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cidis @ cidis @ |
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280 |
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Kevin E. Muñoz Loberlly N. Salazar Steven S. Araujo Boris X. Vintimilla |
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Title |
Detecting and Characterizing Human Interactions to EnhanceHuman-Robot Engagement |
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Conference Article |
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2025 |
Publication |
3rd International Conference on Robotics, Control and Vision Engineering RCVE 2025 |
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cidis @ cidis @ |
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281 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |

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Title |
Image patch similarity through a meta-learning metric based approach |
Type |
Conference Article |
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Year |
2019 |
Publication |
15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia |
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511-517 |
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Abstract  |
Comparing images regions are one of the core methods used on computer vision for tasks like image classification, scene understanding, object detection and recognition. Hence, this paper proposes a novel approach to determine similarity of image regions (patches), in order to obtain the best representation of image patches. This problem has been studied by many researchers presenting different approaches, however, the ability to find the better criteria to measure the similarity on image regions are still a challenge. The present work tackles this problem using a few-shot metric based meta-learning framework able to compare image regions and determining a similarity measure to decide if there is similarity between the compared patches. Our model is training end-to-end from scratch. Experimental results
have shown that the proposed approach effectively estimates the similarity of the patches and, comparing it with the state of the art approaches, shows better results. |
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gtsi @ user @ |
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115 |
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Author |
Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla |

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Title |
Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. |
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Journal Article |
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Year |
2015 |
Publication |
Revista Tecnológica ESPOL-RTE |
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Vol. 28 |
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pp. 1-7 |
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Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb |
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Abstract  |
Comúnmente durante la rehabilitación física, el diagnóstico dado por el especialista se basa en observaciones cualitativas que sugieren, en algunos casos, conclusiones subjetivas. El presente trabajo propone un enfoque cuantitativo, orientado a servir de ayuda a fisioterapeutas, a través de una herramienta interactiva y de bajo costo que permite medir los movimientos de miembros superiores. Estos movimientos son capturados por un sensor RGB-D y procesados mediante la metodología propuesta, dando como resultado una eficiente representación de movimientos, permitiendo la evaluación cuantitativa de movimientos de los miembros superiores. |
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ESPOL |
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English |
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English |
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Call Number |
cidis @ cidis @ |
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39 |
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Author |
Marjorie Chalen; Boris X. Vintimilla |

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Title |
Towards Action Prediction Applying Deep Learning |
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Journal Article |
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Year |
2019 |
Publication |
Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 |
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pp. 1-3 |
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action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm. |
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Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task. |
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cidis @ cidis @ |
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129 |
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Author |
Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic |

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Title |
Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles |
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Journal Article |
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2016 |
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Journal of Automation and Control Engineering (JOACE) |
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Vol. 4 |
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pp. 430-436 |
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Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System |
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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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English |
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cidis @ cidis @ |
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51 |
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