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Author | Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla | ||||
Title | An approach to automatic assistance in physiotherapy based on on-line movement identification. | Type | Conference Article | ||
Year | 2012 | Publication | VI Andean Region International Conference – ANDESCON 2012 | Abbreviated Journal | |
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Keywords | patient rehabilitation, patient treatment, statistical analysis | ||||
Abstract | This paper describes a method for on-line movement identification, oriented to patient’s movement evaluation during physiotherapy. An analysis based on Mahalanobis distance between temporal windows is performed to identify the “idle/motion” state, which defines the beginning and end of the patient’s movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments. | ||||
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Publisher | IEEE | Place of Publication | Andean Region International Conference (ANDESCON), 2012 VI | Editor | |
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Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 24 | ||
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Author | Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla | ||||
Title | Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. | Type | Journal Article | ||
Year | 2015 | Publication | Revista Tecnológica ESPOL-RTE | Abbreviated Journal | |
Volume | Vol. 28 | Issue | Pages | pp. 1-7 | |
Keywords | Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb | ||||
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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Publisher | ESPOL | Place of Publication | Editor | ||
Language | English | Summary Language | English | Original Title | |
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Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 39 | ||
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Author | Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic | ||||
Title | Sensor Fault Detection and Diagnosis for autonomous vehicles | Type | Conference Article | ||
Year | 2015 | Publication | 2nd International Conference on Mechatronics, Automation and Manufacturing (ICMAM 2015), International Conference on, Singapur, 2015 | Abbreviated Journal | |
Volume | 30 | Issue | MATEC Web of Conferences | Pages | 1-6 |
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Abstract | In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor. | ||||
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Publisher | EDP Sciences | Place of Publication | Editor | ||
Language | English | Summary Language | English | Original Title | |
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Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 42 | ||
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Author | Mildred Cruz; Cristhian A. Aguilera; Boris X. Vintimilla; Ricardo Toledo; Ángel D. Sappa | ||||
Title | Cross-spectral image registration and fusion: an evaluation study | Type | Conference Article | ||
Year | 2015 | Publication | 2nd International Conference on Machine Vision and Machine Learning | Abbreviated Journal | |
Volume | 331 | Issue | Pages | ||
Keywords | multispectral imaging; image registration; data fusion; infrared and visible spectra | ||||
Abstract | This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented. | ||||
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Publisher | Computer Vision Center | Place of Publication | Barcelona, Spain | Editor | |
Language | English | Summary Language | English | Original Title | |
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Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 35 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture | Type | Conference Article | ||
Year | 2017 | Publication | 19th International Conference on Image Analysis and Processing. | Abbreviated Journal | |
Volume | Issue | Pages | 287-297 | ||
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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 66 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Learning Image Vegetation Index through a Conditional Generative Adversarial Network | Type | Conference Article | ||
Year | 2017 | Publication | 2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) | Abbreviated Journal | |
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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 70 | ||
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Author | Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero | ||||
Title | Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. | Type | Conference Article | ||
Year | 2018 | Publication | IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador | Abbreviated Journal | |
Volume | Issue | Pages | 1-6 | ||
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Abstract | 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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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 87 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud | ||||
Title | Deep Learning based Single Image Dehazing | Type | Conference Article | ||
Year | 2018 | Publication | 14th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2018. Salt Lake City, Utah. USA | Abbreviated Journal | |
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Abstract | This paper proposes a novel approach to remove haze degradations in RGB images using a stacked conditional Generative Adversarial Network (GAN). It employs a triplet of GAN to remove the haze on each color channel independently. A multiple loss functions scheme, applied over a conditional probabilistic model, is proposed. The proposed GAN architecture learns to remove the haze, using as conditioned entrance, the images with haze from which the clear images will be obtained. Such formulation ensures a fast model training convergence and a homogeneous model generalization. Experiments showed that the proposed method generates high-quality clear images. |
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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 83 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Vegetation Index Estimation from Monospectral Images | Type | Conference Article | ||
Year | 2018 | Publication | 15th International Conference, Image Analysis and Recognition (ICIAR 2018), Póvoa de Varzim, Portugal. Lecture Notes in Computer Science | Abbreviated Journal | |
Volume | 10882 | Issue | Pages | 353-362 | |
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Abstract | This paper proposes a novel approach to estimate Normalized Difference Vegetation Index (NDVI) from just the red channel of a RGB image. The NDVI index is defined as the ratio of the difference of the red and infrared radiances over their sum. In other words, information from the red channel of a RGB image and the corresponding infrared spectral band are required for its computation. In the current work the NDVI index is estimated just from the red channel by training a Conditional Generative Adversarial Network (CGAN). The architecture proposed for the generative network consists of a single level structure, which combines at the final layer results from convolutional operations together with the given red channel with Gaussian noise to enhance details, resulting in a sharp NDVI image. Then, the discriminative model estimates the probability that the NDVI generated index came from the training dataset, rather than the index automatically generated. Experimental results with a large set of real images are provided showing that a Conditional GAN single level model represents an acceptable approach to estimate NDVI index. |
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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 82 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud | ||||
Title | Near InfraRed Imagery Colorization | Type | Conference Article | ||
Year | 2018 | Publication | 25 th IEEE International Conference on Image Processing, ICIP 2018 | Abbreviated Journal | |
Volume | Issue | Pages | 2237-2241 | ||
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Abstract | This paper proposes a stacked conditional Generative Adversarial Network-based method for Near InfraRed (NIR) imagery colorization. We propose a variant architecture of Generative Adversarial Network (GAN) that uses multiple loss functions over a conditional probabilistic generative model. We show that this new architecture/loss-function yields better generalization and representation of the generated colored IR images. The proposed approach is evaluated on a large test dataset and compared to recent state of the art methods using standard metrics.1 Index Terms—Convolutional Neural Networks (CNN), Generative Adversarial Network (GAN), Infrared Imagery colorization. |
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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 81 | ||
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