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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
	Volume		Issue		Pages
	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.
	Address
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication	Andean Region International Conference (ANDESCON), 2012 VI	Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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.
	Address
	Corporate Author				Thesis
	Publisher	ESPOL	Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher	EDP Sciences	Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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.
	Address
	Corporate Author				Thesis
	Publisher	Computer Vision Center	Place of Publication	Barcelona, Spain	Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Volume		Issue		Pages
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	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
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	gtsi @ user @			Serial	81
Permanent link to this record