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Author |
Patricia Suarez, Angel D. Sappa |
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Title |
A Generative Model for Guided Thermal Image Super-Resolution |
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Conference Article |
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2024 |
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In 19th International Conference on Computer Vision Theory and Applications VISAPP 2024 |
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cidis @ cidis @ |
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240 |
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Author |
Henry Velesaca Lara, Patricia Suarez, Darío Carpio & Angel Sappa |
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Title |
Fruit Grading based on Deep Learning and Active Vision System |
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Conference Article |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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cidis @ cidis @ |
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241 |
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Author |
Henry Velesaca Lara, Juan Antonio Holgado & José Miguel Gutiérrez |
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Title |
Optimizing Smart Factory Operations: A Methodological Approach to Industrial System Implementation based on OPC-UA |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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cidis @ cidis @ |
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242 |
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Author |
Patricia Suarez, Angel Sappa |
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Title |
Depth-Conditioned Thermal-like Image Generation |
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Conference Article |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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cidis @ cidis @ |
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243 |
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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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Conference Article |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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no |
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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 Siamese Architecture and CNN Models |
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Conference Article |
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Year |
2024 |
Publication |
Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
245 |
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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. |
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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 |
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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14234 LNCS |
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369 - 380 |
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ISSN |
03029743 |
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978-303143152-4 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
231 |
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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) |
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2023-May |
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9749 - 9756 |
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ISSN |
10504729 |
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979-835032365-8 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
206 |
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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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Vol. 2020-June |
Issue |
11 |
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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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