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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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Velesaca, H. O., Suárez, P. L., Sappa, A. D., Carpio, D., Rivadeneira, R. E., & Sanchez, A. (2022). Review on Common Techniques for Urban Environment Video Analytics. In WORKSHOP BRASILEIRO DE CIDADES INTELIGENTES (WBCI 2022) (pp. 107–118).
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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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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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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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Rafael E. Rivadeneira, A. D. S., Vintimilla B. X. and Hammoud R. (2022). A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. Sensors, Vol. 22(Issue 6).
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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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