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Author Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al.
Title Thermal Image Super-Resolution Challenge Results- PBVS 2022. Type Conference Article
Year 2022 Publication Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE
Volume (down) 2022-June Issue Pages 349-357
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Abstract 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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Call Number cidis @ cidis @ Serial 175
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Author Rangnekar,Aneesha; Mulhollan,Zachary; Vodacek,Anthony; Hoffman,Matthew; Sappa,Angel D.; Yu,Jun et al.
Title Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. Type Conference Article
Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE
Volume (down) 2022-June Issue Pages 389-397
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Notes Approved no
Call Number cidis @ cidis @ Serial 176
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Author Low S., Inkawhich N., Nina O., Sappa A. and Blasch E.
Title Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. Type Conference Article
Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE
Volume (down) 2022-June Issue Pages 417-425
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Abstract 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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Notes Approved no
Call Number cidis @ cidis @ Serial 177
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Author Velez R., Paredes A., Silva S., Paillacho D., and Paillacho J.
Title Implementation of a UVC lights disinfection system for a diferential robot applying security methods in indoor. Type Conference Article
Year 2022 Publication Communications in Computer and Information Science, International Conference on Applied Technologies (ICAT 2021), octubre 27-29 Abbreviated Journal CONFERENCE
Volume (down) 1535 Issue Pages 319-331
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Notes Approved no
Call Number cidis @ cidis @ Serial 178
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