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Author |
Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa |
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Title |
Corn Kernel Classification From Few Training Samples |
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Journal Article |
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Year |
2023 |
Publication |
In journal Artificial Intelligence in Agriculture |
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Vol. 9 |
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pp. 89-99 |
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25897217 |
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Call Number |
cidis @ cidis @ |
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223 |
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Author |
Armin Mehri; Parichehr Behjati; Angel Domingo Sappa |
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Title |
TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution. |
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Journal Article |
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Year |
2023 |
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IEEE Access |
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Vol. 11 |
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pp. 11529-11540 |
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21693536 |
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cidis @ cidis @ |
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207 |
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Author |
Armin Mehri, Parichehr Behjati, Dario Carpio, and Angel D. Sappa |
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Title |
SRFormer: Efficient Yet Powerful Transformer Network For Single Image Super Resolution |
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Journal Article |
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Year |
2023 |
Publication |
IEEE access |
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Vol. 11 |
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Pages |
121457 - 121469 |
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21693536 |
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cidis @ cidis @ |
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227 |
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Author |
Abel Rubio, Wilton Agila, Leandro González & Jonathan Aviles-Cedeno |
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Title |
Distributed Intelligence in Autonomous PEM Fuel Cell Control. |
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Journal Article |
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Year |
2023 |
Publication |
Energies 2023 |
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Vol. 16 |
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Issue 12 |
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19961073 |
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cidis @ cidis @ |
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217 |
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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 |
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Journal Article |
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Year |
2020 |
Publication |
Sensors 2020 |
Abbreviated Journal |
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Volume |
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 @ |
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132 |
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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 |
Abbreviated Journal |
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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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Permanent link to this record |
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Author |
Cristhian A. Aguilera; Cristhian Aguilera; Angel D. Sappa |
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Title |
Melamine faced panels defect classification beyond the visible spectrum. |
Type |
Journal Article |
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Year |
2018 |
Publication |
In Sensors 2018 |
Abbreviated Journal |
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Volume |
Vol. 11 |
Issue |
Issue 11 |
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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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no |
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Call Number |
gtsi @ user @ |
Serial |
89 |
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Author |
Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa |
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Title |
Fine-tuning deep convolutional networks for lepidopterous genus recognition |
Type |
Journal Article |
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Year |
2017 |
Publication |
Lecture Notes in Computer Science |
Abbreviated Journal |
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Volume |
Vol. 10125 LNCS |
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Pages |
pp. 467-475 |
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no |
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Call Number |
gtsi @ user @ |
Serial |
63 |
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Author |
Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo |
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Title |
Cross-Spectral Local Descriptors via Quadruplet Network |
Type |
Journal Article |
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Year |
2017 |
Publication |
In Sensors Journal |
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Volume |
Vol. 17 |
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Pages |
pp. 873 |
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Call Number |
gtsi @ user @ |
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64 |
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Author |
Victor Santos; Angel D. Sappa; Miguel Oliveira |
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Title |
Special Issue on Autonomous Driving an Driver Assistance Systems |
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Journal Article |
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Year |
2017 |
Publication |
In Robotics and Autonomous Systems Journal |
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Vol. 91 |
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pp. 208-209 |
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gtsi @ user @ |
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65 |
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