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Henry O. Velesaca, P. L. S., Dario Carpio, Rafael E. Rivadeneira, Ángel Sánchez, Angel D. Sappa. (2022). Video Analytics in Urban Environments: Challenges and Approaches. In ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series (Vol. 224, pp. 101–122).
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Jorge L. Charco, A. D. S., Boris X. Vintimilla, Henry O. Velesaca. (2022). Human Body Pose Estimation in Multi-view Environments. In ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series (Vol. 224, pp. 79–99).
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Ulises Gildardo Quiroz Antúnez, A. I. M. R., María Fernanda Calderón Vega, Adán Guillermo Ramírez García. (2022). APTITUDE OF COFFEE (COFFEA ARABICA L.) AND CACAO (THEOBROMA CACAO L.) CROPS CONSIDERING CLIMATE CHANGE. Granja, Vol. 36(Issue 2).
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Roberto Jacome Galarza. (2022). Multimodal deep learning for crop yield prediction. In Doctoral Symposium on Information and Communication Technologies –DSICT 2022. Octubre 12-14. (Vol. 1647, pp. 106–117).
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Rangnekar, A., Mulhollan, Z., Vodacek, A., Hoffman, M., Sappa, A. D., & Yu, J. et al. (2022). Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. In Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. (Vol. 2022-June, pp. 389–397).
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Low S., I. N., Nina O., Sappa A. and Blasch E. (2022). Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. In Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. (Vol. 2022-June, pp. 417–425).
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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Rafael E. Rivadeneira, A. D. S., Boris X. Vintimilla, Jin Kim, Dogun Kim et al. (2022). Thermal Image Super-Resolution Challenge Results- PBVS 2022. In Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. (Vol. 2022-June, pp. 349–357).
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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Velez R., P. A., Silva S., Paillacho D., and Paillacho J. (2022). Implementation of a UVC lights disinfection system for a diferential robot applying security methods in indoor. In Communications in Computer and Information Science, International Conference on Applied Technologies (ICAT 2021), octubre 27-29 (Vol. 1535, pp. 319–331).
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Rivadeneira, R. E., & Sappa, A. D. and V. B. X. (2022). Thermal Image Super-Resolution: A Novel Unsupervised Approach. In 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 (Vol. 1474, pp. 495–506).
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Benítez-Quintero J., Q. - P. O., Calderon, Fernanda. (2022). Notes on Sulfur Fluxes in Urban Areas with Industrial Activity. In 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022, (Vol. 2022-July).
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