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Author |
Rafael E. Rivadeneira, Angel Domingo Sappa, Vintimilla B. X. and Hammoud R. |
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Title |
A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. |
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2022 |
Publication |
Sensors |
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Sensors |
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Vol. 22 |
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Issue 6 |
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Call Number |
cidis @ cidis @ |
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170 |
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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. |
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Journal Article |
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2020 |
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In Sensors |
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Vol. 2020-August |
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16 |
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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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Call Number |
cidis @ cidis @ |
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133 |
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Author |
Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al. |
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Title |
Thermal Image Super-Resolution Challenge Results- PBVS 2022. |
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Conference Article |
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Year |
2022 |
Publication |
Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
Abbreviated Journal |
CONFERENCE |
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2022-June |
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349-357 |
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This paper presents results from the third Thermal Image
Super-Resolution (TISR) challenge organized in the Perception Beyond the Visible Spectrum (PBVS) 2022 workshop.
The challenge uses the same thermal image dataset as the
first two challenges, with 951 training images and 50 validation images at each resolution. A set of 20 images was
kept aside for testing. The evaluation tasks were to measure
the PSNR and SSIM between the SR image and the ground
truth (HR thermal noisy image downsampled by four), and
also to measure the PSNR and SSIM between the SR image
and the semi-registered HR image (acquired with another
camera). The results outperformed those from last year’s
challenge, improving both evaluation metrics. This year,
almost 100 teams participants registered for the challenge,
showing the community’s interest in this hot topic. |
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cidis @ cidis @ |
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175 |
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Author |
Rangnekar,Aneesha; Mulhollan,Zachary; Vodacek,Anthony; Hoffman,Matthew; Sappa,Angel D.; Yu,Jun et al. |
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Title |
Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. |
Type |
Conference Article |
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Year |
2022 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
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CONFERENCE |
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2022-June |
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389-397 |
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no |
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cidis @ cidis @ |
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176 |
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Author |
Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. |
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Title |
Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. |
Type |
Conference Article |
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Year |
2022 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
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CONFERENCE |
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2022-June |
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417-425 |
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This paper details the results and main findings of the
second iteration of the Multi-modal Aerial View Object
Classification (MAVOC) challenge. This year’s MAVOC
challenge is the second iteration. The primary goal of
both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) input
modalities. Teams are encouraged/challenged to develop
multi-modal approaches that incorporate complementary
information from both domains. While the 2021 challenge
showed a proof of concept that both modalities could be
used together, the 2022 challenge focuses on the detailed
multi-modal models. Using the same UNIfied COincident
Optical and Radar for recognitioN (UNICORN) dataset and
competition format that was used in 2021. Specifically, the
challenge focuses on two techniques, (1) SAR classification
and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods
and describing their performance on our blind test set. Notably, all of the top ten teams outperform our baseline. For
SAR classification, the top team showed a 129% improvement over our baseline and an 8% average improvement
from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average
improvement over 2021. |
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Call Number |
cidis @ cidis @ |
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177 |
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Author |
Velez R., Paredes A., Silva S., Paillacho D., and Paillacho J. |
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Title |
Implementation of a UVC lights disinfection system for a diferential robot applying security methods in indoor. |
Type |
Conference Article |
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Year |
2022 |
Publication |
Communications in Computer and Information Science, International Conference on Applied Technologies (ICAT 2021), octubre 27-29 |
Abbreviated Journal |
CONFERENCE |
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Volume |
1535 |
Issue |
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Pages |
319-331 |
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cidis @ cidis @ |
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178 |
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Author |
Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X. |
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Title |
Thermal Image Super-Resolution: A Novel Unsupervised Approach. |
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2022 |
Publication |
Communications in Computer and Information Science, 15th International Communications in Computer and Information Science Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
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BOOK |
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1474 |
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495-506 |
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cidis @ cidis @ |
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179 |
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Author |
Henry O. Velesaca, Patricia L. Suárez, Dario Carpio, Rafael E. Rivadeneira, Ángel Sánchez, Angel D. Sappa. |
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Title |
Video Analytics in Urban Environments: Challenges and Approaches. |
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Book Chapter |
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2022 |
Publication |
ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series |
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BOOK |
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224 |
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101-122 |
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cidis @ cidis @ |
Serial |
196 |
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Author |
Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla, Henry O. Velesaca. |
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Title |
Human Body Pose Estimation in Multi-view Environments. |
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2022 |
Publication |
ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series |
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BOOK |
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224 |
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79-99 |
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Call Number |
cidis @ cidis @ |
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197 |
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Author |
Angel D. Sappa. |
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Title |
ICT Applications for Smart Cities |
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2022 |
Publication |
Intelligent Systems Reference Library |
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224 |
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cidis @ cidis @ |
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198 |
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