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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 |
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Volume |
Vol. 2020-June |
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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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14248220 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
132 |
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Author |
Armin Mehri; Angel D. Sappa |
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Title |
Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples |
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Conference Article |
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Year |
2019 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States |
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971-979 |
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Abstract |
This paper presents a novel approach for colorizing
near infrared (NIR) images. The approach is based on
image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored
networks that require less computation times, converge
faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation
metrics—and qualitatively evaluated showing considerable
improvements with respect to the state of the art |
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Call Number |
gtsi @ user @ |
Serial |
105 |
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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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121457 - 121469 |
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21693536 |
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no |
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Call Number |
cidis @ cidis @ |
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227 |
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Author |
Angel Morera; Angel Sánchez; Angel D. Sappa; José F. Vélez |
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Title |
Robust Detection of Outdoor Urban Advertising Panels in Static Images. |
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Conference Article |
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Year |
2019 |
Publication |
17th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2019); Ávila, España. Communications in Computer and Information Science |
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1047 |
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Pages |
246-256 |
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Abstract |
One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising
panels. For such a purpose, a previous stage is to accurately detect and
locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based
on a deep neural network architecture that minimizes the number of
false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection
over Union (IoU) accuracy metric make this proposal applicable in real
complex urban images. |
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no |
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Call Number |
gtsi @ user @ |
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107 |
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Author |
Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez |
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Title |
SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. |
Type |
Journal Article |
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Year |
2020 |
Publication |
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Abbreviated Journal |
In Sensors |
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Volume |
Vol. 2020-August |
Issue |
16 |
Pages |
pp. 1-23 |
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Keywords |
object detection; urban outdoor panels; one-stage detectors; Single Shot MultiBox Detector (SSD); You Only Look Once (YOLO); detection metrics; object and scene imaging variabilities |
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Abstract |
This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO)
deep neural networks for the outdoor advertisement panel detection problem by handling multiple
and combined variabilities in the scenes. Publicity panel detection in images o ers important
advantages both in the real world as well as in the virtual one. For example, applications like Google
Street View can be used for Internet publicity and when detecting these ads panels in images, it could
be possible to replace the publicity appearing inside the panels by another from a funding company.
In our experiments, both SSD and YOLO detectors have produced acceptable results under variable
sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex
background and multiple panels in scenes. Due to the diculty of finding annotated images for the
considered problem, we created our own dataset for conducting the experiments. The major strength
of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable
when the publicity contained inside the panel is analyzed after detecting them. On the other side,
YOLO produced better panel localization results detecting a higher number of True Positive (TP)
panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models
with di erent types of semantic segmentation networks and using the same evaluation metrics is
also included. |
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English |
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14248220 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
133 |
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Author |
Angel J. Valencia; Roger M. Idrovo; Angel D. Sappa; Douglas Plaza G.; Daniel Ochoa |
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Title |
A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers |
Type |
Conference Article |
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Year |
2017 |
Publication |
2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) |
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1-6 |
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Call Number |
cidis @ cidis @ |
Serial |
60 |
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Author |
Angel D. Sappa; Cristhian A. Aguilera; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |
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Title |
Monocular visual odometry: a cross-spectral image fusion based approach |
Type |
Journal Article |
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Year |
2016 |
Publication |
Robotics and Autonomous Systems Journal |
Abbreviated Journal |
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Volume |
Vol. 86 |
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Pages |
pp. 26-36 |
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Keywords |
Monocular visual odometry LWIR-RGB cross-spectral imaging Image fusion |
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Abstract |
This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is em- pirically obtained by means of a mutual information based evaluation met- ric. The objective is to have a exible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odom- etry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
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Call Number |
cidis @ cidis @ |
Serial |
54 |
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Author |
Angel D. Sappa. |
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Title |
ICT Applications for Smart Cities |
Type |
Book Chapter |
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Year |
2022 |
Publication |
Intelligent Systems Reference Library |
Abbreviated Journal |
BOOK |
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224 |
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cidis @ cidis @ |
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198 |
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Author |
Angel D. Sappa, Spencer Low, Oliver Nina, Erik Blasch, Dylan Bowald & Nathan Inkawhich |
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Title |
Multi-modal Aerial View Image Challenge: Sensor Domain Translation |
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Conference Article |
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2024 |
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Accepted in 20th IEEE Workshop on Perception Beyond the Visible Spectrum of the 2024 Conference on Computer Vision and Pattern Recognition |
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Call Number |
cidis @ cidis @ |
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235 |
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Angel D. Sappa, Spencer Low, Oliver Nina, Erik Blasch, Dylan Bowald & Nathan Inkawhich |
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Title |
Multi-modal Aerial View Image Challenge: SAR Classification |
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Conference Article |
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2024 |
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Accepted in 20th IEEE Workshop on Perception Beyond the Visible Spectrum of the 2024 Conference on Computer Vision and Pattern Recognition |
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cidis @ cidis @ |
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234 |
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