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Author | Marjorie Chalen; Boris X. Vintimilla | ||||
Title | Towards Action Prediction Applying Deep Learning | Type | Journal Article | ||
Year | 2019 | Publication | Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 | Abbreviated Journal | |
Volume | Issue | Pages | pp. 1-3 | ||
Keywords | action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm. | ||||
Abstract | Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task. | ||||
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Call Number | cidis @ cidis @ | Serial | 129 | ||
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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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Call Number | cidis @ cidis @ | Serial | 39 | ||
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Author | Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho | ||||
Title | Development of animated facial expression to express emotions in a robot: RobotIcon. | Type | Conference Article | ||
Year | 2017 | Publication | IEEE Ecuador Technical Chapter Meeting (ETCM) | Abbreviated Journal | |
Volume | 2017-January | Issue | Pages | 1-6 | |
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Call Number | gtsi @ user @ | Serial | 71 | ||
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Author | Luis Chuquimarca, Renzo Pacheco, Paula Gonzalez, Boris Vintimilla & Sergio Velastin | ||||
Title | Fruit defect detection using CNN models with real and virtual data. | Type | Conference Article | ||
Year | 2023 | Publication | Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 | Abbreviated Journal | |
Volume | Issue | Pages | 272 - 279 | ||
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Call Number | cidis @ cidis @ | Serial | 203 | ||
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Author | Luis Chuquimarca, Boris Vintimilla & Sergio Velastin | ||||
Title | Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets. | Type | Conference Article | ||
Year | 2023 | Publication | Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 | Abbreviated Journal | |
Volume | Issue | Pages | 536 - 543 | ||
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Call Number | cidis @ cidis @ | Serial | 202 | ||
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Author | Luis C. Herrera, Leslie del R. Lima, Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. | ||||
Title | Metrics Design of Usability and Behavior Analysis of a Human-Robot-Game Platform. | Type | Conference Article | ||
Year | 2021 | Publication | The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communication in Computer and Information Science | Abbreviated Journal | |
Volume | 1388 | Issue | Pages | 164-178 | |
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Call Number | cidis @ cidis @ | Serial | 191 | ||
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Author | Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. | ||||
Title | Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. | Type | Conference Article | ||
Year | 2022 | Publication | Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. | Abbreviated Journal | CONFERENCE |
Volume | 2022-June | Issue | Pages | 417-425 | |
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Abstract | This paper details the results and main findings of the second iteration of the Multi-modal Aerial View Object Classification (MAVOC) challenge. This year’s MAVOC challenge is the second iteration. The primary goal of both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) input modalities. Teams are encouraged/challenged to develop multi-modal approaches that incorporate complementary information from both domains. While the 2021 challenge showed a proof of concept that both modalities could be used together, the 2022 challenge focuses on the detailed multi-modal models. Using the same UNIfied COincident Optical and Radar for recognitioN (UNICORN) dataset and competition format that was used in 2021. Specifically, the challenge focuses on two techniques, (1) SAR classification and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods and describing their performance on our blind test set. Notably, all of the top ten teams outperform our baseline. For SAR classification, the top team showed a 129% improvement over our baseline and an 8% average improvement from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average improvement over 2021. |
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Call Number | cidis @ cidis @ | Serial | 177 | ||
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Author | Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa | ||||
Title | Fine-tuning deep convolutional networks for lepidopterous genus recognition | Type | Journal Article | ||
Year | 2017 | Publication | Lecture Notes in Computer Science | Abbreviated Journal | |
Volume | Vol. 10125 LNCS | Issue | Pages | pp. 467-475 | |
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Call Number | gtsi @ user @ | Serial | 63 | ||
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Author | José Reyes; Axel Godoy; Miguel Realpe. | ||||
Title | Uso de software de código abierto para fusión de imágenes agrícolas multiespectrales adquiridas con drones. | Type | Conference Article | ||
Year | 2019 | Publication | International Multi-Conference of Engineering, Education and Technology (LACCEI 2019); Montego Bay, Jamaica | Abbreviated Journal | |
Volume | 2019-July | Issue | Pages | ||
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Abstract | Los drones o aeronaves no tripuladas son muy útiles para la adquisición de imágenes, de forma mucho más simple que los satélites o aviones. Sin embargo, las imágenes adquiridas por drones deben ser combinadas de alguna forma para convertirse en información de valor sobre un terreno o cultivo. Existen diferentes programas que reciben imágenes y las combinan en una sola imagen, cada uno con diferentes características (rendimiento, precisión, resultados, precio, etc.). En este estudio se revisaron diferentes programas de código abierto para fusión de imágenes, con el ?n de establecer cuál de ellos es más útil, especí?camente para ser utilizado por pequeños y medianos agricultores en Ecuador. Los resultados pueden ser de interés para diseñadores de software, ya que al utilizar código abierto, es posible modi?car e integrar los programas en un ?ujo de trabajo más simpli?cado. Además, que permite disminuir costos debido a que no requiere de pagos de licencias para su uso, lo cual puede repercutir en un mayor acceso a la tecnología para los pequeños y medianos agricultores. Como parte de los resultados de este estudio se ha creado un repositorio de acceso público con algoritmos de pre-procesamiento necesarios para manipular las imágenes adquiridas por una cámara multiespectral y para luego obtener un mapa completo en formatos RGB, CIR y NDVI. | ||||
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Call Number | gtsi @ user @ | Serial | 102 | ||
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Author | Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa | ||||
Title | Deep learning based camera pose estimation in multi-view environment. | Type | Conference Article | ||
Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) | Abbreviated Journal | |
Volume | Issue | Pages | 224-228 | ||
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Abstract | 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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Notes | Approved | no | |||
Call Number | gtsi @ user @ | Serial | 93 | ||
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