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Author |
Morocho-Cayamcela, M.E. |
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Title |
Increasing the Segmentation Accuracy of Aerial Images with Dilated Spatial Pyramid Pooling |
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Journal Article |
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2020 |
Publication |
Electronic Letters on Computer Vision and Image Analysis (ELCVIA) |
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Vol. 19 |
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Issue 2 |
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pp. 17-21 |
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cidis @ cidis @ |
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140 |
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Author |
Patricia L. Suarez |
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Title |
Procesamiento y representación de imágenes multiespectrales usando técnicas de aprendizaje profundo (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). Ph.D. thesis. |
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Book Chapter |
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2020 |
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Ediciones FIEC-ESPOL. |
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Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector. |
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Español |
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cidis @ cidis @ |
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144 |
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Author |
Rosero Vasquez Shendry |
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Title |
Facial recognition: traditional methods vs. methods based on deep learning. Advances in Intelligent Systems and Computing – Information Technology and Systems Proceedings of ICITS 2020. |
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Journal Article |
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Year |
2020 |
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Pages |
615-625 |
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cidis @ cidis @ |
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145 |
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Author |
Viñán-Ludeña, M.S., Roberto Jacome Galarza, Montoya, L.R., Leon, A.V., & Ramírez, C.C. |
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Title |
Smart university: an architecture proposal for information management using open data for research projects. |
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Journal Article |
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2020 |
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Advances in Intelligent Systems and Computing |
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1137 AISC, 2020 |
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172-178 |
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Call Number |
cidis @ cidis @ |
Serial |
188 |
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Author |
Steven Silva, Dennys Paillacho., David Soque, María Guerra & Jonathan Paillacho |
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Title |
Autonomous Intelligent Navigation For Mobile Robots In Closed Environments. |
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Conference Article |
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Year |
2021 |
Publication |
The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science |
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1388 |
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Pages |
391-402 |
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no |
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cidis @ cidis @ |
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187 |
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Author |
Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. |
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Title |
Camera pose estimation in multi-view environments:from virtual scenarios to the real world |
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Journal Article |
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Year |
2021 |
Publication |
In Image and Vision Computing Journal. (Article number 104182) |
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Vol. 110 |
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Keywords |
Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments |
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Abstract |
This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired
images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of
overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly
trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the
relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity
on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the
scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used,
highlighting the importance on the similarity between virtual-real scenarios. |
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English |
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English |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
147 |
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Author |
Mehri, A, Ardakani, P.B., Sappa, A.D. |
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Title |
MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution. |
Type |
Conference Article |
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Year |
2021 |
Publication |
In IEEE Winter Conference on Applications of Computer Vision WACV 2021, enero 5-9, 2021 |
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Pages |
2703-2712 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
148 |
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Author |
Mehri, A, Ardakani, P.B., Sappa, A.D. |
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Title |
LiNet: A Lightweight Network for Image Super Resolution |
Type |
Conference Article |
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Year |
2021 |
Publication |
25th International Conference on Pattern Recognition (ICPR), enero 10-15, 2021 |
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Pages |
7196-7202 |
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Call Number |
cidis @ cidis @ |
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149 |
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Author |
Jacome-Galarza L.-R |
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Title |
Crop yield prediction utilizing multimodal deep learning |
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Conference Article |
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Year |
2021 |
Publication |
16th Iberian Conference on Information Systems and Technologies, CISTI 2021, junio 23 – 26, 2021 |
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Keywords |
Agricultura de precisión; sensores remotos; aprendizaje profundo multimodal; IoT; agentes inteligentes; computación aplicada. |
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Abstract |
La agricultura de precisión es una práctica vital para
mejorar la producción de cosechas. El presente trabajo tiene
como objetivo desarrollar un modelo multimodal de aprendizaje
profundo que es capaz de producir un mapa de salud de
cosechas. El modelo recibe como entradas imágenes multiespectrales
y datos de sensores de campo (humedad,
temperatura, estado del suelo, etc.) y crea un mapa de
rendimiento de la cosecha. La utilización de datos multimodales
tiene como finalidad extraer patrones ocultos del estado de salud
de las cosechas y de esta manera obtener mejores resultados que
los obtenidos mediante los índices de vegetación. |
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cidis @ cidis @ |
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150 |
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Author |
Rivadeneira R.E., Sappa A.D., Vintimilla B.X., Nathan S., Kansal P., Mehri A et al. |
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Title |
Thermal Image Super-Resolution Challenge – PBVS 2021. |
Type |
Conference Article |
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Year |
2021 |
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In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021., junio 19 – 25, 2021 |
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4354-4362 |
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cidis @ cidis @ |
Serial |
151 |
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