S
Salviano Soares
Researcher at University of Trás-os-Montes and Alto Douro
Publications - 82
Citations - 645
Salviano Soares is an academic researcher from University of Trás-os-Montes and Alto Douro. The author has contributed to research in topics: Computer science & Interpolation. The author has an hindex of 9, co-authored 74 publications receiving 514 citations.
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Journal ArticleDOI
Sun, wind and water flow as energy supply for small stationary data acquisition platforms
Raul Morais,Samuel G. Matos,Miguel A. Fernandes,António Valente,Salviano Soares,Paulo J. S. G. Ferreira,Manuel J. C. S. Reis +6 more
TL;DR: Experimental results prove that the prototype, the MPWiNodeX, can manage simultaneously the three energy sources for charging a NiMH battery pack, resulting in an almost perpetual operation of the evaluated ZigBee network router.
Proceedings ArticleDOI
Classification of Images of Childhood Pneumonia using Convolutional Neural Networks.
Arata Andrade Saraiva,Nuno M. F. Ferreira,Luciano Lopes de Sousa,Nator Junior C. Costa,Jose Vigno Moura Sousa,D. B. S. Santos,António Valente,Salviano Soares +7 more
TL;DR: A comparative classification of Pneumonia using Convolution Neural Network using the dataset Labeled Optical Coherence Tomography and Chest X-Ray Images for Classification with an average accuracy of 95.30 % was described.
Journal ArticleDOI
Impact sound insulation technique using corn cob particleboard
Jorge Faustino,Luís Torres Pereira,Salviano Soares,Daniel Cruz,Anabela Paiva,Anabela Paiva,Humberto Varum,José Ferreira,Jorge Pinto +8 more
TL;DR: A low technological corn cob particleboard has been under research by as discussed by the authors, which intends to be affordable and sustainable, and evaluated the impact sound insulation potential of the proposed particleboard, which indicated that the proposed product may also have an interesting acoustic behaviour for building purposes.
Proceedings ArticleDOI
Coexistence and Interference Tests on a Bluetooth Low Energy Front-End.
TL;DR: This study analysis the impact of a BLE sensor network on a crowded 2.4GHz room, with multiple Wi-Fi routers, ZigBee sensors and Bluetooth technology, and compares the results with the ones obtained inside an anechoic chamber on similar experiences.
Proceedings ArticleDOI
Models of Learning to Classify X-ray Images for the Detection of Pneumonia using Neural Networks.
Arata Andrade Saraiva,D. B. S. Santos,Nator Junior C. Costa,Jose Vigno Moura Sousa,Nuno M. F. Ferreira,António Valente,Salviano Soares +6 more
TL;DR: A comparison of two neural networks, the multilayer perceptron and Neural Network, for the detection and classification of pneumonia, using the Chest-X-Ray data set provided by Kermany et al., 2018.