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Angel D. Sappa, Spencer Low, Oliver Nina, Erik Blasch, Dylan Bowald & Nathan Inkawhich |
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Title |
Multi-modal Aerial View Image Challenge: Sensor Domain Translation |
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2024 |
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Accepted in 20th IEEE Workshop on Perception Beyond the Visible Spectrum of the 2024 Conference on Computer Vision and Pattern Recognition |
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cidis @ cidis @ |
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235 |
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Author |
Patricia Suarez & Angel D. Sappa |
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Title |
Haze-Free Imaging through Haze-Aware Transformer Adaptations |
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2024 |
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In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) |
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cidis @ cidis @ |
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236 |
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Author |
Rafael Rivadeneira, Henry Velesaca & Angel Sappa |
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Title |
Cross-Spectral Image Registration: a Comparative Study and a New Benchmark Dataset |
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2024 |
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In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) |
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cidis @ cidis @ |
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237 |
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Tyrone Rodríguez, Adriana Guilindro, Paolo Piedrahita & Miguel Realpe |
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Title |
Towards Birds Conservation in Dry Forest Ecosystems through Audio Recognition via Deep Learning |
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2024 |
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In 9th International Congress on Information and Communication Technology ICICT 2024 |
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cidis @ cidis @ |
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239 |
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Author |
Patricia Suarez, Angel D. Sappa |
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Title |
A Generative Model for Guided Thermal Image Super-Resolution |
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2024 |
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In 19th International Conference on Computer Vision Theory and Applications VISAPP 2024 |
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cidis @ cidis @ |
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240 |
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Henry Velesaca Lara, Patricia Suarez, Darío Carpio & Angel Sappa |
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Title |
Fruit Grading based on Deep Learning and Active Vision System |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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cidis @ cidis @ |
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241 |
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Author |
Henry Velesaca Lara, Juan Antonio Holgado & José Miguel Gutiérrez |
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Title |
Optimizing Smart Factory Operations: A Methodological Approach to Industrial System Implementation based on OPC-UA |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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cidis @ cidis @ |
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242 |
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Author |
Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco |
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Title |
Computer vision for image understanding. A comprehensive review |
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2019 |
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International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador |
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248-259 |
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Computer Vision has its own Turing test: Can a machine describe the contents of an image or a video in the way a human being would do? In this paper, the progress of Deep Learning for image recognition is analyzed in order to know the answer to this question. In recent years, Deep Learning has increased considerably the precision rate of many tasks related to computer vision. Many datasets of labeled images are now available online, which leads to pre-trained models for many computer vision applications. In this work, we gather information of the latest techniques to perform image understanding and description. As a conclusion we obtained that the combination of Natural Language Processing (using Recurrent Neural Networks and Long Short-Term Memory) plus Image Understanding (using Convolutional Neural Networks) could bring new types of powerful and useful applications in which the computer will be able to answer questions about the content of images and videos. In order to build datasets of labeled images, we need a lot of work and most of the datasets are built using crowd work. These new applications have the potential to increase the human machine interaction to new levels of usability and user’s satisfaction. |
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gtsi @ user @ |
Serial |
97 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture |
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2017 |
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19th International Conference on Image Analysis and Processing. |
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287-297 |
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gtsi @ user @ |
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66 |
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Byron Lima; Ricardo Cajo; Victor Huilcapi; Wilton Agila |
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Title |
Modeling and comparative study of linear and nonlinear controllers for rotary inverted pendulum |
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2017 |
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Journal of Physics: Conference Series |
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783 |
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The rotary inverted pendulum (RIP) is a problem difficult to control, several studies have been conducted where different control techniques have been applied. Literature reports that, although problem is nonlinear, classical PID controllers presents appropriate performances when applied to the system. In this paper, a comparative study of the performances of linear and nonlinear PID structures is carried out. The control algorithms are evaluated in the RIP system, using indices of performance and power consumption, which allow the categorization of control strategies according to their performance. This article also presents the modeling system, which has been estimated some of the parameters involved in the RIP system, using computer-aided design tools (CAD) and experimental methods or techniques proposed by several authors attended. The results indicate a better performance of the nonlinear controller with an increase in the robustness and faster response than the linear controller |
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English |
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gtsi @ user @ |
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69 |
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