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Author |
Dennys Paillacho, Nayeth Solórzano, Michael Arce, María Plues & Edwin Eras |
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Title |
Advanced metrics to evaluate autistic children's attention and emotions from facial characteristics using a human robot-game interface |
Type |
Conference Article |
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Year |
2023 |
Publication |
Communications in Computer and Information Science. 11th Conferencia Ecuatoriana de Tecnologías de la Información y Comunicación (TICEC 2023) Cuenca 18-20 Octubre 2023 |
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Vol. 1885 CCIS |
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Pages |
234 - 247 |
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18650929 |
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978-303145437-0 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
221 |
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Author |
Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa |
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Title |
Fast CNN Stereo Depth Estimation through Embedded GPU Devices |
Type |
Journal Article |
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Year |
2020 |
Publication |
Sensors 2020 |
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Volume |
Vol. 2020-June |
Issue |
11 |
Pages |
pp. 1-13 |
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Keywords |
stereo matching; deep learning; embedded GPU |
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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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English |
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English |
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14248220 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
132 |
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Author |
Henry O. Velesaca, Gisel Bastidas, Mohammad Rouhani, Angel D. Sappa |
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Title |
Multimodal image registration techniques: a comprehensive survey |
Type |
Journal Article |
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Year |
2024 |
Publication |
Multimedia Tools and Applications |
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Volume |
Vol. 83 |
Issue |
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Pages |
63919 - 63947 |
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13807501 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
248 |
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Author |
Steven Silva, Nervo Verdezoto, Dennys Paillacho, Samuel Millan-Norman & Juan David Hernandez |
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Title |
Online Social Robot Navigation in Indoor, Large and Crowded Environments. |
Type |
Conference Article |
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Year |
2023 |
Publication |
IEEE International Conference on Robotics and Automation (ICRA 2023) Londres, 29 may 2023 – 2 jun 2023 |
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Volume |
2023-May |
Issue |
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Pages |
9749 - 9756 |
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ISSN |
10504729 |
ISBN |
979-835032365-8 |
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Approved |
no |
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Call Number |
cidis @ cidis @ |
Serial |
206 |
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Author |
Emmanuel Moran, Boris Vintimilla & Miguel Realpe |
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Title |
Towards a Robust Solution for the Supermarket Shelf Audit Problem. |
Type |
Conference Article |
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Year |
2023 |
Publication |
26th Iberoamerican Congress on Pattern Recognition (CIARP 2023) Coimbra 27-30 November 2023 |
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Volume |
Vol. 14469 LNCS |
Issue |
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Pages |
257-271 |
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ISSN |
03029743 |
ISBN |
978-303149017-0 |
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Approved |
no |
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Call Number |
cidis @ cidis @ |
Serial |
204 |
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Author |
Suarez Patricia; Carpio Dario; Sappa Angel D. |
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Title |
A Deep Learning Based Approach for Synthesizing Realistic Depth Maps |
Type |
Conference Article |
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Year |
2023 |
Publication |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics 22nd International Conference on Image Analysis and Processing, ICIAP 2023 Udine 11 – 15 September 2023 |
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Volume |
14234 LNCS |
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Pages |
369 - 380 |
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03029743 |
ISBN |
978-303143152-4 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
231 |
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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 |
Type |
Conference Article |
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Year |
2024 |
Publication |
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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ISSN |
03029743 |
ISBN |
978-303149017-0 |
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Approved |
no |
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Call Number |
cidis @ cidis @ |
Serial |
249 |
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Author |
Tommy David Beltran Borbor, Raul Josue Villao Rodriguez, Luis Enrique Chuquimarca Jiménez, Boris Xavier Vintimilla Burgos & Sergio Alejandro Velastin |
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Title |
Fruit Deformity Classification through Single-Input and Multi-Input Architectures based on CNN Models using Real and Synthetic Images |
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Conference Article |
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Year |
2025 |
Publication |
Lecture Notes in Computer Science: 27th The Iberomican Congress on Pattern Recognition CIARP 2024 Talca 26 – 29 Noviembre 2024 |
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Vol. 15368 LNCS |
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46-62 |
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ISSN |
03029743 |
ISBN |
978-303176606-0 |
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Approved |
no |
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Call Number |
cidis @ cidis @ |
Serial |
251 |
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Author |
Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia |
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Title |
Dense extreme inception network for edge detection. |
Type |
Journal Article |
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Year |
2023 |
Publication |
Pattern Recognition |
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Volume |
Vol. 139 |
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ISSN |
00313203 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
216 |
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Author |
Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco |
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Title |
Computer vision for image understanding. A comprehensive review |
Type |
Conference Article |
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Year |
2019 |
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International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador |
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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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no |
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Call Number |
gtsi @ user @ |
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97 |
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