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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title Learning to Colorize Infrared Images Type Conference Article
Year 2017 Publication 15th International Conference on Practical Applications of Agents and Multi-Agent Systems Abbreviated Journal
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Call Number cidis @ cidis @ Serial 58
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Author Cristhian A. Aguilera; Xaver Soria; Angel D. Sappa; Ricardo Toledo
Title RGBN Multispectral Images: a Novel Color Restoration Approach Type Conference Article
Year 2017 Publication 15th International Conference on Practical Applications of Agents and Multi-Agent Systems Abbreviated Journal
Volume 619 Issue Pages 155-163
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Call Number cidis @ cidis @ Serial 59
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Author Angel J. Valencia; Roger M. Idrovo; Angel D. Sappa; Douglas Plaza G.; Daniel Ochoa
Title A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers Type Conference Article
Year 2017 Publication 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) Abbreviated Journal
Volume Issue Pages 1-6
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Call Number cidis @ cidis @ Serial 60
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Author Dennis G. Romero; Roberto Yoncon; Angel Guale; Bonny Bayot; Fanny Panchana
Title Evaluación de técnicas de clasificación orientadas a la identificación automática de órganos del camarón a partir de imágenes histológicas Type Conference Article
Year 2017 Publication 15th LACCEI International Multi-Conference for Engineering, Education, and Technology Abbreviated Journal
Volume 2017-July Issue Pages 1-6
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Call Number cidis @ cidis @ Serial 61
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title Infrared Image Colorization based on a Triplet DCGAN Architecture. Type Conference Article
Year 2017 Publication 13th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2017. (This paper has been selected as “Best Paper Award” ) Abbreviated Journal
Volume 2017-July Issue Pages 212-217
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Call Number cidis @ cidis @ Serial 62
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Author Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa
Title Deep learning based camera pose estimation in multi-view environment. Type Conference Article
Year 2018 Publication 14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) Abbreviated Journal
Volume Issue Pages 224-228
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Abstract This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose.
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Call Number gtsi @ user @ Serial 93
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Author Alex Ferrin; Julio Larrea; Miguel Realpe; Daniel Ochoa
Title Detection of utility poles from noisy Point Cloud Data in Urban environments. Type Conference Article
Year 2018 Publication Artificial Intelligence and Cloud Computing Conference (AICCC 2018) Abbreviated Journal
Volume Issue Pages 53-57
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Abstract In recent years 3D urban maps have become more common, thus providing complex point clouds that include diverse urban furniture such as pole-like objects. Utility poles detection in urban environment is of particular interest for electric utility companies in order to maintain an updated inventory for better planning and management. The present study develops an automatic method for the detection of utility poles from noisy point cloud data of Guayaquil – Ecuador, where many poles are located next to buildings, or houses are built until the border of the sidewalk getting very close to poles, which increases the difficulty of discriminating poles, walls, columns, fences and building corners.
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Call Number gtsi @ user @ Serial 94
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Author Marjorie Chalen; Boris X. Vintimilla
Title Towards Action Prediction Applying Deep Learning Type Journal Article
Year 2019 Publication Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 Abbreviated Journal
Volume Issue Pages pp. 1-3
Keywords action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm.
Abstract Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task.
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Call Number cidis @ cidis @ Serial 129
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Author Armin Mehri; Angel D. Sappa
Title Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples Type Conference Article
Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal
Volume Issue Pages 971-979
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Abstract This paper presents a novel approach for colorizing

near infrared (NIR) images. The approach is based on

image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored

networks that require less computation times, converge

faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation

metrics—and qualitatively evaluated showing considerable

improvements with respect to the state of the art
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Call Number gtsi @ user @ Serial 105
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud
Title Image Vegetation Index through a Cycle Generative Adversarial Network Type Conference Article
Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal
Volume Issue Pages 1014-1021
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Abstract This paper proposes a novel approach to estimate the

Normalized Difference Vegetation Index (NDVI) just from

an RGB image. The NDVI values are obtained by using

images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The

cycled GAN network is able to obtain a NIR image from

a given gray scale image. It is trained by using unpaired

set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are

obtained from the provided RGB images). Then, the NIR

image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous

approaches are also provided.
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Call Number gtsi @ user @ Serial 106
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