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Author | Patricia Suarez, Angel Sappa | ||||
Title | Depth-Conditioned Thermal-like Image Generation | Type | Conference Article | ||
Year | 2024 | Publication | Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) | Abbreviated Journal | |
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Call Number | cidis @ cidis @ | Serial | 243 | ||
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Author | Omar Coello, Moisés Coronel, Darío Carpio, Boris X. Vintimilla & Luis Chuquimarca | ||||
Title | Enhancing Apple’s Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging | Type | Conference Article | ||
Year | 2024 | Publication | Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) | Abbreviated Journal | |
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Call Number | cidis @ cidis @ | Serial | 244 | ||
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Author | Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin | ||||
Title | Classifying Healthy and Defective Fruits with a Siamese Architecture and CNN Models | Type | Conference Article | ||
Year | 2024 | Publication | Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) | Abbreviated Journal | |
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Call Number | cidis @ cidis @ | Serial | 245 | ||
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Author | Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias; A. Paulo Moreira | ||||
Title | Incremental Texture Mapping for Autonomous Driving | Type | Journal Article | ||
Year | 2016 | Publication | Robotics and Autonomous Systems Journal | Abbreviated Journal | |
Volume | Vol. 84 | Issue | Pages | pp. 113-128 | |
Keywords | Scene reconstruction, Autonomous driving, Texture mapping | ||||
Abstract | Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures. | ||||
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Language | English | Summary Language | English | Original Title | |
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Call Number | cidis @ cidis @ | Serial | 50 | ||
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Author | G.A. Rubio; Wilton Agila | ||||
Title | Sustainable Energy: A Strategic View of Fuel Cells | Type | Conference Article | ||
Year | 2019 | Publication | 8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania | Abbreviated Journal | |
Volume | Issue | Pages | 239-243 | ||
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Abstract | Based on the model of the proton exchange fuel cell in a strategic context, this document develops the issue of energy as one of the pillars to achieve the sustainability of our planet, considering the future scenarios up to the year 2060 of the situation energy, hydrogen as a strategic vector and the contribution of the fuel cell in solving the serious problems of environmental pollution and economic inequity that humanity faces; for its application in the energy generation, telecommunications and vehicle manufacturing industries. |
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Call Number | gtsi @ user @ | Serial | 110 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Image patch similarity through a meta-learning metric based approach | Type | Conference Article | ||
Year | 2019 | Publication | 15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia | Abbreviated Journal | |
Volume | Issue | Pages | 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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Call Number | gtsi @ user @ | Serial | 115 | ||
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Author | Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco | ||||
Title | Computer vision for image understanding. A comprehensive review | Type | Conference Article | ||
Year | 2019 | Publication | International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador | Abbreviated Journal | |
Volume | Issue | Pages | 248-259 | ||
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Abstract | Computer Vision has its own Turing test: Can a machine describe the contents of an image or a video in the way a human being would do? In this paper, the progress of Deep Learning for image recognition is analyzed in order to know the answer to this question. In recent years, Deep Learning has increased considerably the precision rate of many tasks related to computer vision. Many datasets of labeled images are now available online, which leads to pre-trained models for many computer vision applications. In this work, we gather information of the latest techniques to perform image understanding and description. As a conclusion we obtained that the combination of Natural Language Processing (using Recurrent Neural Networks and Long Short-Term Memory) plus Image Understanding (using Convolutional Neural Networks) could bring new types of powerful and useful applications in which the computer will be able to answer questions about the content of images and videos. In order to build datasets of labeled images, we need a lot of work and most of the datasets are built using crowd work. These new applications have the potential to increase the human machine interaction to new levels of usability and user’s satisfaction. | ||||
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Call Number | gtsi @ user @ | Serial | 97 | ||
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Author | Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla | ||||
Title | Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. | Type | Journal Article | ||
Year | 2015 | Publication | Revista Tecnológica ESPOL-RTE | Abbreviated Journal | |
Volume | Vol. 28 | Issue | Pages | pp. 1-7 | |
Keywords | Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb | ||||
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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Publisher | ESPOL | Place of Publication | Editor | ||
Language | English | Summary Language | English | Original Title | |
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Call Number | cidis @ cidis @ | Serial | 39 | ||
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Author | Marjorie Chalen; Boris X. Vintimilla | ||||
Title | Towards Action Prediction Applying Deep Learning | Type | Journal Article | ||
Year | 2019 | Publication | Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 | Abbreviated Journal | |
Volume | Issue | Pages | pp. 1-3 | ||
Keywords | action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm. | ||||
Abstract | 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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Call Number | cidis @ cidis @ | Serial | 129 | ||
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Author | Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa | ||||
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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ISSN | 14248220 | ISBN | Medium | ||
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Call Number | cidis @ cidis @ | Serial | 132 | ||
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