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Henry Velesaca Lara, Patricia Suarez, Darío Carpio & Angel Sappa |
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Fruit Grading based on Deep Learning and Active Vision System |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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no |
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cidis @ cidis @ |
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241 |
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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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Conference Article |
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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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no |
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cidis @ cidis @ |
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236 |
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Author |
Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla |
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Title |
Human Pose Estimation through A Novel Multi-View Scheme |
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Conference Article |
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2022 |
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Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 |
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5 |
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855-862 |
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Multi-View Scheme, Human Pose Estimation, Relative Camera Pose, Monocular Approach |
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This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human
pose estimation problem. The proposed approach first obtains the human body joints of a set of images,
which are captured from different views at the same time. Then, it enhances the obtained joints by using a
multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from
another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed
for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and
comparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements
in the accuracy of body joints estimations. |
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yes |
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cidis @ cidis @ |
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169 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Image patch similarity through a meta-learning metric based approach |
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Conference Article |
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2019 |
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15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia |
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511-517 |
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Comparing images regions are one of the core methods used on computer vision for tasks like image classification, scene understanding, object detection and recognition. Hence, this paper proposes a novel approach to determine similarity of image regions (patches), in order to obtain the best representation of image patches. This problem has been studied by many researchers presenting different approaches, however, the ability to find the better criteria to measure the similarity on image regions are still a challenge. The present work tackles this problem using a few-shot metric based meta-learning framework able to compare image regions and determining a similarity measure to decide if there is similarity between the compared patches. Our model is training end-to-end from scratch. Experimental results
have shown that the proposed approach effectively estimates the similarity of the patches and, comparing it with the state of the art approaches, shows better results. |
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no |
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gtsi @ user @ |
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115 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud |
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Title |
Image Vegetation Index through a Cycle Generative Adversarial Network |
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Conference Article |
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2019 |
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Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States |
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1014-1021 |
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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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no |
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gtsi @ user @ |
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106 |
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Author |
Velez R., Paredes A., Silva S., Paillacho D., and Paillacho J. |
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Title |
Implementation of a UVC lights disinfection system for a diferential robot applying security methods in indoor. |
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Conference Article |
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Year |
2022 |
Publication |
Communications in Computer and Information Science, International Conference on Applied Technologies (ICAT 2021), octubre 27-29 |
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CONFERENCE |
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1535 |
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319-331 |
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no |
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cidis @ cidis @ |
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178 |
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Author |
Xavier Soria; Angel D. Sappa |
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Improving Edge Detection in RGB Images by Adding NIR Channel. |
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2018 |
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14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) |
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266-273 |
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no |
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Call Number |
gtsi @ user @ |
Serial |
95 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Infrared Image Colorization based on a Triplet DCGAN Architecture. |
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Conference Article |
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2017 |
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13th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2017. (This paper has been selected as “Best Paper Award” ) |
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2017-July |
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212-217 |
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no |
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Call Number |
cidis @ cidis @ |
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62 |
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Author |
Jorge Alvarez Tello; Mireya Zapata; Dennys Paillacho |
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Title |
Kinematic optimization of a robot head movements for the evaluation of human-robot interaction in social robotics. |
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Conference Article |
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2019 |
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10th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences (AHFE 2019), Washington D.C.; United States. Advances in Intelligent Systems and Computing |
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975 |
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108-118 |
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This paper presents the simplification of the head movements from
the analysis of the biomechanical parameters of the head and neck at the
mechanical and structural level through CAD modeling and construction with
additive printing in ABS/PLA to implement non-verbal communication strategies and establish behavior patterns in the social interaction. This is using in the
denominated MASHI (Multipurpose Assistant robot for Social Human-robot
Interaction) experimental robotic telepresence platform, implemented by a
display with a fish-eye camera along with the mechanical mechanism, which
permits 4 degrees of freedom (DoF). In the development of mathematicalmechanical modeling for the kinematics codification that governs the robot and
the autonomy of movement, we have the Pitch, Roll, and Yaw movements, and
the combination of all of them to establish an active communication through
telepresence. For the computational implementation, it will be show the rotational matrix to describe the movement. |
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yes |
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gtsi @ user @ |
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108 |
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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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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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cidis @ cidis @ |
Serial |
48 |
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