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Author |
Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa |

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Title |
Deep learning based camera pose estimation in multi-view environment. |
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Conference Article |
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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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224-228 |
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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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gtsi @ user @ |
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93 |
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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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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” ) |
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2017-July |
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212-217 |
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cidis @ cidis @ |
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62 |
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Author |
Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla |

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Title |
Deep learning-based vegetation index estimation |
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Book Chapter |
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2021 |
Publication |
Generative Adversarial Networks for Image-to-Image Translation Book. |
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Chapter 9 |
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Issue 2 |
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205-232 |
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cidis @ cidis @ |
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137 |
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Author |
Angely Oyola; Dennis G. Romero; Boris X. Vintimilla |

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Title |
A Dijkstra-based algorithm for selecting the Shortest-Safe Evacuation Routes in dynamic environments (SSER) |
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Conference Article |
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2017 |
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The 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017) |
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131-135 |
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cidis @ cidis @ |
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55 |
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Author |
Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla |

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Title |
Thermal Image Super-Resolution: a Novel Architecture and Dataset |
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Conference Article |
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Year |
2020 |
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The 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020); Valletta, Malta; 27-29 Febrero 2020 |
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4 |
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111-119 |
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Thermal images, Far Infrared, Dataset, Super-Resolution. |
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This paper proposes a novel CycleGAN architecture for thermal image super-resolution, together with a large
dataset consisting of thermal images at different resolutions. The dataset has been acquired using three thermal
cameras at different resolutions, which acquire images from the same scenario at the same time. The thermal
cameras are mounted in rig trying to minimize the baseline distance to make easier the registration problem.
The proposed architecture is based on ResNet6 as a Generator and PatchGAN as Discriminator. The novelty
on the proposed unsupervised super-resolution training (CycleGAN) is possible due to the existence of aforementioned thermal images—images of the same scenario with different resolutions. The proposed approach
is evaluated in the dataset and compared with classical bicubic interpolation. The dataset and the network are
available. |
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978-989758402-2 |
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gtsi @ user @ |
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121 |
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Author |
Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla, Henry O. Velesaca. |

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Title |
Human Body Pose Estimation in Multi-view Environments. |
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Book Chapter |
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Year |
2022 |
Publication |
ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series |
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BOOK |
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224 |
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79-99 |
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Call Number |
cidis @ cidis @ |
Serial |
197 |
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Author |
Sianna Puente; Cindy Madrid; Miguel Realpe; Boris X. Vintimilla |

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Title |
An Empirical Comparison of DCNN libraries to implement the Vision Module of a Danger Management System |
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Conference Article |
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Year |
2017 |
Publication |
2017 International Conference on Deep Learning Technologies (ICDLT 2017) |
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Part F128535 |
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60-65 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
56 |
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Author |
Angel D. Sappa; Cristhian A. Aguilera; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |


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Title |
Monocular visual odometry: a cross-spectral image fusion based approach |
Type |
Journal Article |
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Year |
2016 |
Publication |
Robotics and Autonomous Systems Journal |
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Volume |
Vol. 86 |
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Pages  |
pp. 26-36 |
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Keywords |
Monocular visual odometry LWIR-RGB cross-spectral imaging Image fusion |
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Abstract |
This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is em- pirically obtained by means of a mutual information based evaluation met- ric. The objective is to have a exible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odom- etry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
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Call Number |
cidis @ cidis @ |
Serial |
54 |
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Author |
Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero |

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Title |
Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. |
Type |
Conference Article |
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Year |
2018 |
Publication |
IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador |
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1-6 |
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The identification of shrimp organs in biology using
histological images is a complex task. Shrimp histological images
poses a big challenge due to their texture and similarity among
classes. Image classification by using feature engineering and
convolutional neural networks (CNN) are suitable methods to
assist biologists when performing organ detection. This work
evaluates the Bag-of-Visual-Words (BOVW) and Pyramid-Bagof-
Words (PBOW) models for image classification leveraging big
data techniques; and transfer learning for the same classification
task by using a pre-trained CNN. A comparative analysis
of these two different techniques is performed, highlighting
the characteristics of both approaches on the shrimp organs
identification problem. |
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gtsi @ user @ |
Serial |
87 |
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Author |
Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla |

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Title |
Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. |
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Journal Article |
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Year |
2015 |
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Revista Tecnológica ESPOL-RTE |
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Vol. 28 |
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pp. 1-7 |
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Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb |
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Abstract |
Comúnmente durante la rehabilitación física, el diagnóstico dado por el especialista se basa en observaciones cualitativas que sugieren, en algunos casos, conclusiones subjetivas. El presente trabajo propone un enfoque cuantitativo, orientado a servir de ayuda a fisioterapeutas, a través de una herramienta interactiva y de bajo costo que permite medir los movimientos de miembros superiores. Estos movimientos son capturados por un sensor RGB-D y procesados mediante la metodología propuesta, dando como resultado una eficiente representación de movimientos, permitiendo la evaluación cuantitativa de movimientos de los miembros superiores. |
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ESPOL |
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English |
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English |
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Call Number |
cidis @ cidis @ |
Serial |
39 |
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