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Author |
Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia |
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Title  |
Dense extreme inception network for edge detection. |
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2023 |
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Pattern Recognition |
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Vol. 139 |
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00313203 |
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cidis @ cidis @ |
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216 |
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Henry Velesaca, Boris Vintimilla, Jorge Vulgarin, Coen Antens & Alberto Rubio Pérez |
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Title |
Deep Learning-based Multimodal Sensing Framework for AntiSpoofing Systems |
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2024 |
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In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) |
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cidis @ cidis @ |
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238 |
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Author |
Boris Vintimilla, Jorge Vulgarin, Henry Velesaca |
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Title |
Deep Learning-based Human Height Estimation from a Stereo Vision System |
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2023 |
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IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) 2023, julio 4-7 |
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979-835033337-4 |
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cidis @ cidis @ |
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215 |
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Author |
Patricia Suarez, Henry Velesaca, Dario Carpio, Angel Sappa, Patricia Urdiales, Francisca Burgos |
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Title |
Deep Learning based Shrimp Classification |
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2022 |
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17th International Symposium on Visual Computing, San Diego, USA, Octubre 3-5. Lecture Notes in Computer Science (LNCS) |
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13598 LNCS |
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36-45 |
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cidis @ cidis @ |
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194 |
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Author |
Patricia L. Suárez, Angel D. Sappa, Boris X. Vintimilla |
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Title |
Cycle generative adversarial network: towards a low-cost vegetation index estimation |
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Conference Article |
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Year |
2021 |
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IEEE International Conference on Image Processing (ICIP 2021) |
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2021-September |
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2783-2787 |
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CyclicGAN, NDVI, near infrared spectra, instance normalization. |
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This paper presents a novel unsupervised approach to estimate the Normalized Difference Vegetation Index (NDVI).The NDVI is obtained as the ratio between information from the visible and near infrared spectral bands; in the current work, the NDVI is estimated just from an image of the visible spectrum through a Cyclic Generative Adversarial Network (CyclicGAN). This unsupervised architecture learns to estimate the NDVI index by means of an image translation between the red channel of a given RGB image and the NDVI unpaired index’s image. The translation is obtained by means of a ResNET architecture and a multiple loss function. Experimental results obtained with this unsupervised scheme show the validity of the implemented model. Additionally, comparisons with the state of the art approaches are provided showing improvements with the proposed approach. |
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cidis @ cidis @ |
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164 |
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Author |
Rafael Rivadeneira, Henry Velesaca & Angel Sappa |
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Title |
Cross-Spectral Image Registration: a Comparative Study and a New Benchmark Dataset |
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Conference Article |
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Year |
2024 |
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In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) |
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cidis @ cidis @ |
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237 |
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Author |
Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa |
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Title |
Corn Kernel Classification From Few Training Samples |
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Journal Article |
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Year |
2023 |
Publication |
In journal Artificial Intelligence in Agriculture |
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Vol. 9 |
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pp. 89-99 |
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25897217 |
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cidis @ cidis @ |
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223 |
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Author |
Michael Teutsch, Angel Sappa & Riad Hammoud |
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Title |
Computer Vision in the Infrared Spectrum: Challenges and ApproachesComputer Vision in the Infrared Spectrum: Challenges and Approaches |
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2021 |
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Synthesis Lectures on Computer Vision |
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Vol. 10 No. 2 |
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pp. 138 |
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cidis @ cidis @ |
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166 |
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Author |
Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin |
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Title |
Classifying Healthy and Defective Fruits with a Siamese Architecture and CNN Models |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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cidis @ cidis @ |
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245 |
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Author |
Patricia L. Suarez, Dario Carpio, Angel Sappa |
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Title |
Boosting Guided Super-Resolution Performance with Synthesized Images |
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2023 |
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17th International Conference On Signal Image Technology & Internet Based Systems |
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cidis @ cidis @ |
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225 |
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