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Author Steven Silva, Dennys Paillacho., David Soque, María Guerra & Jonathan Paillacho
Title Autonomous Intelligent Navigation For Mobile Robots In Closed Environments. Type Conference Article
Year 2021 Publication The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science Abbreviated Journal
Volume 1388 Issue Pages 391-402
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Call Number cidis @ cidis @ Serial 187
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Author Mehri, A, Ardakani, P.B., Sappa, A.D.
Title MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution. Type Conference Article
Year 2021 Publication In IEEE Winter Conference on Applications of Computer Vision WACV 2021, enero 5-9, 2021 Abbreviated Journal
Volume Issue Pages 2703-2712
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Call Number cidis @ cidis @ Serial 148
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Author Mehri, A, Ardakani, P.B., Sappa, A.D.
Title LiNet: A Lightweight Network for Image Super Resolution Type Conference Article
Year 2021 Publication 25th International Conference on Pattern Recognition (ICPR), enero 10-15, 2021 Abbreviated Journal
Volume Issue Pages 7196-7202
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Call Number cidis @ cidis @ Serial 149
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Author Rivadeneira R.E., Sappa A.D., Vintimilla B.X., Nathan S., Kansal P., Mehri A et al.
Title Thermal Image Super-Resolution Challenge – PBVS 2021. Type Conference Article
Year 2021 Publication In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021., junio 19 – 25, 2021 Abbreviated Journal
Volume Issue Pages 4354-4362
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Call Number cidis @ cidis @ Serial 151
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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 Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza
Title Open innovation at university: a systematic literature review Type Journal Article
Year 2020 Publication Advances in Intelligent Systems and Computing Abbreviated Journal
Volume 1159 AISC, 2020 Issue Pages 3-14
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Call Number cidis @ cidis @ Serial 189
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Author Viñán-Ludeña M.S., De Campos L.M., Roberto Jacome Galarza, & Sinche Freire, J.
Title Social media influence: a comprehensive review in general and in tourism domain Type Journal Article
Year 2020 Publication Smart Innovation, Systems and Technologies. Abbreviated Journal
Volume 171, 2020 Issue Pages 25-35
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Call Number cidis @ cidis @ Serial 190
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Author Jacome-Galarza L.-R., Realpe Robalino M.-A., Paillacho Corredores J., Benavides Maldonado J.-L.
Title Time series in sensor data using state of the art deep learning approaches: A systematic literature review. Type Conference Article
Year 2022 Publication VII International Conference on Science, Technology and Innovation for Society (CITIS 2021), mayo 26-28.  Smart Innovation, Systems and Technologies. Abbreviated Journal
Volume 252 Issue Pages 503-514
Keywords time series, deep learning, recurrent networks, sensor data, IoT.
Abstract IoT (Internet of Things) and AI (Artificial Intelligence) are becoming

support tools for several current technological solutions due to significant advancements of these areas. The development of the IoT in various technological fields has contributed to predicting the behavior of various systems such as mechanical, electronic, and control using sensor networks. On the other hand, deep learning architectures have achieved excellent results in complex tasks, where patterns have been extracted in time series. This study has reviewed the most efficient deep learning architectures for forecasting and obtaining trends over time, together with data produced by IoT sensors. In this way, it is proposed to contribute to applications in fields in which IoT is contributing a technological advance such as smart cities, industry 4.0, sustainable agriculture, or robotics. Among the architectures studied in this article related to the process of time series data we have: LSTM (Long Short-Term Memory) for its high precision in prediction and the ability to automatically process input sequences; CNN (Convolutional Neural Networks) mainly in human activity

recognition; hybrid architectures in which there is a convolutional layer for data pre-processing and RNN (Recurrent Neural Networks) for data fusion from different sensors and their subsequent classification; and stacked LSTM Autoencoders that extract the variables from time series in an unsupervised way without the need of manual data pre-processing.Finally, well-known technologies in natural language processing are also used in time series data prediction, such as the attention mechanism and embeddings obtaining promising results.
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Call Number cidis @ cidis @ Serial 152
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Author Rafael E. Rivadeneira, Angel Domingo Sappa, Vintimilla B. X. and Hammoud R.
Title A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. Type Journal Article
Year 2022 Publication Sensors Abbreviated Journal Sensors
Volume Vol. 22 Issue Issue 6 Pages
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Call Number cidis @ cidis @ Serial 170
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Author Patricia L. Suárez, Angel D. Sappa, Boris X. Vintimilla
Title Cycle generative adversarial network: towards a low-cost vegetation index estimation Type Conference Article
Year 2021 Publication IEEE International Conference on Image Processing (ICIP 2021) Abbreviated Journal
Volume 2021-September Issue Pages 2783-2787
Keywords CyclicGAN, NDVI, near infrared spectra, instance normalization.
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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Call Number cidis @ cidis @ Serial 164
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