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Patricia L. Suarez, D. C., Angel D. Sappa. (2024). Enhancement of Guided Thermal Image Super-Resolution Approaches (Vol. 573).
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Patricia L. Suarez, D. C., Angel D. Sappa and Henry O. Velesaca. (2022). Transformer based Image Dehazing. In 16TH International Conference On Signal Image Technology & Internet Based Systems SITIS 2022. (pp. 148–154).
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Patricia L. Suarez, D. C., Angel Sappa. (2023). Boosting Guided Super-Resolution Performance with Synthesized Images. In 17th International Conference On Signal Image Technology & Internet Based Systems, Bangkok, 8-10 November 2023 (pp. 189–195).
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Patricia L. Suarez, D. C., Angel Sappa. (2023). Depth Map Estimation from a Single 2D Image. In 17th International Conference On Signal Image Technology & Internet Based Systems, Bangkok, 8-10 November 2023 (pp. 347–353).
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Patricia Suarez & Angel D. Sappa. (2024). Haze-Free Imaging through Haze-Aware Transformer Adaptations. In In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024).
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Patricia Suarez & Angel Sappa. (2023). Toward a thermal image-like representation. In Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) Lisbon, 19-21 Febrero 2023 (pp. 133–140).
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Patricia Suarez Riofrio & Angel D. Sappa. (2024). Thermal Image Synthesis: Bridging the Gap between Visible and Infrared Spectrum. In Accepted in 19th International Symposium on Visual Computing 2024.
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Patricia Suarez, A. D. S. (2024). A Generative Model for Guided Thermal Image Super-Resolution. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024) Rome 27 – 29 February 2024 (Vol. Vol. 3: VISAPP, pp. 765–771).
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Patricia Suarez, A. S. (2024). Depth-Conditioned Thermal-like Image Generation. In 14th International Conference on Pattern Recognition Systems (ICPRS).
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Patricia Súarez, H. V., Dario Carpio & Angel Sappa. (2023). Corn Kernel Classification From Few Training Samples. In journal Artificial Intelligence in Agriculture, Vol. 9, pp. 89–99.
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