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Author  |
Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa | ||||
| Title | Fast CNN Stereo Depth Estimation through Embedded GPU Devices | Type | Journal Article | ||
| Year | 2020 | Publication | Sensors 2020 | Abbreviated Journal | |
| Volume | Vol. 2020-June | Issue | 11 | Pages | pp. 1-13 |
| Keywords | stereo matching; deep learning; embedded GPU | ||||
| Abstract | Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it is unknown what is the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models on three different embedded GPU devices, with and without optimization methods, presenting performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically augmenting the runtime speed of current models. In our experiments, we achieve real-time inference speed, in the range of 5–32 ms, for 1216 368 input stereo images on the Jetson TX2, Jetson Xavier, and Jetson Nano embedded devices. |
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| Language | English | Summary Language | English | Original Title | |
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| ISSN | 14248220 | ISBN | Medium | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 132 | ||
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| Author |
Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo | ||||
| Title | Cross-Spectral Local Descriptors via Quadruplet Network | Type | Journal Article | ||
| Year | 2017 | Publication | In Sensors Journal | Abbreviated Journal | |
| Volume | Vol. 17 | Issue | Pages | pp. 873 | |
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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 64 | ||
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| Author |
Cristhian A. Aguilera; Cristhian Aguilera; Angel D. Sappa | ||||
| Title | Melamine faced panels defect classification beyond the visible spectrum. | Type | Journal Article | ||
| Year | 2018 | Publication | In Sensors 2018 | Abbreviated Journal | |
| Volume | Vol. 11 | Issue | Issue 11 | Pages | |
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| Abstract | In this work, we explore the use of images from different spectral bands to classify defects in melamine faced panels, which could appear through the production process. Through experimental evaluation, we evaluate the use of images from the visible (VS), near-infrared (NIR), and long wavelength infrared (LWIR), to classify the defects using a feature descriptor learning approach together with a support vector machine classifier. Two descriptors were evaluated, Extended Local Binary Patterns (E-LBP) and SURF using a Bag of Words (BoW) representation. The evaluation was carried on with an image set obtained during this work, which contained five different defect categories that currently occurs in the industry. Results show that using images from beyond the visual spectrum helps to improve classification performance in contrast with a single visible spectrum solution. |
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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 89 | ||
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| Author |
Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo | ||||
| Title | Learning crossspectral similarity measures with deep convolutional neural networks | Type | Conference Article | ||
| Year | 2016 | Publication | IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 267-275 | ||
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| Abstract | 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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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 48 | ||
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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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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 59 | ||
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| Author |
Cristina L. Abad; Yi Lu; Roy H. Campbell | ||||
| Title | DARE: Adaptive Data Replication for Efficient Cluster Scheduling | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE International Conference on Cluster Computing, 2011 | Abbreviated Journal | |
| Volume | Issue | Pages | 159 - 168 | ||
| Keywords | MapReduce, replication, scheduling, locality | ||||
| Abstract | Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively. | ||||
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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | yes | |||
| Call Number | cidis @ cidis @ | Serial | 21 | ||
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| Author |
Daniela Rato, Miguel Oliviera, Victor Santos, Manuel Gomes & Angel Sappa | ||||
| Title | A Sensor-to-Pattern Calibration Framework for Multi-Modal Industrial Collaborative Cells. | Type | Journal Article | ||
| Year | 2022 | Publication | Journal of Manufacturing Systems | Abbreviated Journal | |
| Volume | Vol. 64 | Issue | Pages | pp. 497-507 | |
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| Notes | Approved | yes | |||
| Call Number | cidis @ cidis @ | Serial | 184 | ||
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| Author |
Del Pino, J.; Salazar, G.; Cedeño, V. Msc. | ||||
| Title | Adaptación de un Recomendador de Filtro Colaborativo Basado en el Usuario para la Creación de un Recomendador de Materias de Pregrado Basado en el Historial Académico de los Estudiantes | Type | Journal Article | ||
| Year | 2011 | Publication | Revista Tecnológica ESPOL | Abbreviated Journal | |
| Volume | Vol. 24 | Issue | Pages | pp. 29 - 34 | |
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| Abstract | Los sistemas de recomendación son ampliamente utilizados hoy en día gracias a su capacidad de analizar las preferencias de usuarios y sugerir ítems. No obstante, el uso de los recomendadores está limitado a un modelo basado en el usuario y no en su historial de preferencias, discriminando así el campo de aplicación, por ejemplo, a sistemas académicos donde sea primordial el estudio de las decisiones del estudiante a lo largo de su carrera. El presente trabajo presenta un esfuerzo por adaptar filtros colaborativos basados en el usuario a filtros colaborativos basados en el historial del usuario. Con un conjunto de pruebas mediremos su efectividad utilizando dos algoritmos distintos de similaridad para recomendar materias a un estudiante en el sexto semestre de la carrera de Ingeniería en Electrónica y Telecomunicaciones ofertada por la FIEC – ESPOL. Los resultados muestran que es factible adaptar un recomendador a un modelo basado en el historial del usuario |
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| Address | Campus “Gustavo Galindo Velasco” La prosperina Km 30,5 vía perimetral, Guayaquil, Ecuador | ||||
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| Language | Español | Summary Language | Español | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 13 | ||
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| Author |
Dennis G. Romero, Anselmo Frizera N., & Teodiano Freire B. | ||||
| Title | Reconocimiento en-línea de acciones humanas basado en patrones de RWE aplicado en ventanas dinámicas de momentos invariantes. | Type | Journal Article | ||
| Year | 2014 | Publication | Revista Iberoamericana de Automática e Informática industrial 00 (2014) | Abbreviated Journal | |
| Volume | Vol. 11 | Issue | Pages | pp. 202-211 | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 220 | ||
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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. | ||||
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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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