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Dennys Paillacho, Nayeth I. Solorzano Alcivar, & Jonathan S. Paillacho Corredores. (2021). LOLY 1.0: A Proposed Human-Robot-Game Platform Architecture for the Engagement of Children with Autism in the Learning Process. In The international Conference on Systems and Information Sciences (ICCIS 2020), julio 27-29. Advances in Intelligent Systems and Computing. (Vol. 1273, pp. 225–238).
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Rivadeneira, R. E., & Sappa, A. D. and V. B. X. (2022). Thermal Image Super-Resolution: A Novel Unsupervised Approach. In Communications in Computer and Information Science, 15th International Communications in Computer and Information Science Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Vol. 1474, pp. 495–506).
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Henry O. Velesaca, P. L. S., Dario Carpio, Rafael E. Rivadeneira, Ángel Sánchez, Angel D. Sappa. (2022). Video Analytics in Urban Environments: Challenges and Approaches. In ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series (Vol. 224, pp. 101–122).
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Jorge L. Charco, A. D. S., Boris X. Vintimilla, Henry O. Velesaca. (2022). Human Body Pose Estimation in Multi-view Environments. In ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series (Vol. 224, pp. 79–99).
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Angel D. Sappa. (2022). ICT Applications for Smart Cities. In Intelligent Systems Reference Library (Vol. 224).
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Dennys Paillacho, N. S., Michael Arce, María Plues & Edwin Eras. (2023). Advanced metrics to evaluate autistic children's attention and emotions from facial characteristics using a human robot-game interface. In Communications in Computer and Information Science. 11th Conferencia Ecuatoriana de Tecnologías de la Información y Comunicación TICEC 2023 (Vol. 1885 CCIS, pp. 234–247).
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Miguel A. Murillo, J. E. A., & Miguel Realpe. (2021). Beyond visual and radio line of sight UAVs monitoring system through open software in a simulated environment. In The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science (Vol. 1388, pp. 629–642).
Abstract: The problem of loss of line of sight when operating drones has be-come a reality with adverse effects for professional and amateur drone opera-tors, since it brings technical problems such as loss of data collected by the de-vice in one or more instants of time during the flight and even misunderstand-ings of legal nature when the drone flies over prohibited or private places. This paper describes the implementation of a drone monitoring system using the In-ternet as a long-range communication network in order to avoid the problem of loss of communication between the ground station and the device. For this, a simulated environment is used through an appropriate open software tool. The operation of the system is based on a client that makes requests to a server, the latter in turn communicates with several servers, each of which has a drone connected to it. In the proposed system when a drone is ready to start a flight, its server informs the main server of the system, which in turn gives feedback to the client informing it that the device is ready to carry out the flight; this way customers can send a mission to the device and keep track of its progress in real time on the screen of their web application.
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Steven Silva, D. P., David Soque, María Guerra & Jonathan Paillacho. (2021). Autonomous Intelligent Navigation For Mobile Robots In Closed Environments. In The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science (Vol. 1388, pp. 391–402).
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Luis C. Herrera, L. del R. L., Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. (2021). Metrics Design of Usability and Behavior Analysis of a Human-Robot-Game Platform. In The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communication in Computer and Information Science (Vol. 1388, pp. 164–178).
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Patricia L. Suárez, A. D. S., Boris X. Vintimilla. (2021). Cycle generative adversarial network: towards a low-cost vegetation index estimation. In IEEE International Conference on Image Processing (ICIP 2021) (Vol. 2021-September, pp. 2783–2787).
Abstract: This paper presents a novel unsupervised approach to estimate the Normalized Difference Vegetation Index (NDVI).The NDVI is obtained as the ratio between information from the visible and near infrared spectral bands; in the current work, the NDVI is estimated just from an image of the visible spectrum through a Cyclic Generative Adversarial Network (CyclicGAN). This unsupervised architecture learns to estimate the NDVI index by means of an image translation between the red channel of a given RGB image and the NDVI unpaired index’s image. The translation is obtained by means of a ResNET architecture and a multiple loss function. Experimental results obtained with this unsupervised scheme show the validity of the implemented model. Additionally, comparisons with the state of the art approaches are provided showing improvements with the proposed approach.
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