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Author |
Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo |
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Title |
Learning crossspectral similarity measures with deep convolutional neural networks |
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Conference Article |
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2016 |
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IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops |
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267-275 |
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The simultaneous use of images from different spectra can be helpful to improve the performance of many com- puter vision tasks. The core idea behind the usage of cross- spectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN archi- tectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Ex- perimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Ad- ditionally, our experiments show that some CNN architec- tures are capable of generalizing between different cross- spectral domains. |
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English |
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English |
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no |
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cidis @ cidis @ |
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48 |
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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 |
Publication |
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 |
Steven Silva, Nervo Verdezoto, Dennys Paillacho, Samuel Millan-Norman & Juan David Hernandez |
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Title |
Online Social Robot Navigation in Indoor, Large and Crowded Environments. |
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Conference Article |
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2023 |
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IEEE International Conference on Robotics and Automation (ICRA 2023) |
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2023-May |
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9749 - 9756 |
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10504729 |
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979-835032365-8 |
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cidis @ cidis @ |
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206 |
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Patricia Suarez, Angel D. Sappa |
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Title |
A Generative Model for Guided Thermal Image Super-Resolution |
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2024 |
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In 19th International Conference on Computer Vision Theory and Applications VISAPP 2024 |
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cidis @ cidis @ |
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240 |
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Author |
Tyrone Rodríguez, Adriana Guilindro, Paolo Piedrahita & Miguel Realpe |
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Title |
Towards Birds Conservation in Dry Forest Ecosystems through Audio Recognition via Deep Learning |
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2024 |
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In 9th International Congress on Information and Communication Technology ICICT 2024 |
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cidis @ cidis @ |
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239 |
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Author |
Velesaca, H.O., Suárez, P. L., Mira, R., & Sappa, A.D. |
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Title |
Computer Vision based Food Grain Classification: a Comprehensive Survey |
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Journal Article |
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Year |
2021 |
Publication |
In Computers and Electronics in Agriculture Journal. (Article number 106287) |
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Vol. 187 |
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cidis @ cidis @ |
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159 |
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Author |
Suárez P. |
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Title |
Processing and Representation of Multispectral Images Using Deep Learning Techniques |
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2021 |
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In Electronic Letters on Computer Vision and Image Analysis |
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Vol. 19 |
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Issue 2 |
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pp. 5-8 |
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Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector |
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Master's thesis |
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Español |
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yes |
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cidis @ cidis @ |
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122 |
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Author |
Patricia Suarez & Angel D. Sappa |
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Title |
Haze-Free Imaging through Haze-Aware Transformer Adaptations |
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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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236 |
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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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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 |
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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