2020
Autores
Roque, J; Santos, JD; Simões, J; Almeida, F;
Publicação
Dynamic Strategic Thinking for Improved Competitiveness and Performance - Advances in Business Strategy and Competitive Advantage
Abstract
2020
Autores
Madureira, AM; Abraham, A; Gandhi, N; Silva, C; Antunes, M;
Publicação
SoCPaR
Abstract
2020
Autores
Madureira, AM; Abraham, A; Gandhi, N; Silva, C; Antunes, M;
Publicação
Advances in Intelligent Systems and Computing
Abstract
2020
Autores
Madureira, AM; Abraham, A; Gandhi, N; Varela, ML;
Publicação
Advances in Intelligent Systems and Computing
Abstract
2020
Autores
Braga, D; Madureira, A;
Publicação
International Journal of Computer Information Systems and Industrial Management Applications
Abstract
The rapid expansion of Asian hornets poses a high threat for the honey bee survival, as these invaders pray on them. Furthermore, they also pose a threat to people who are allergic, whose sting can lead to death. This study proposes a Decision Support System that uses Computer Vision techniques to automatically detect signs of Vespa velutina through images from GPS equipped camera. The goal of the system is to provide timely information about the presence of these invaders, allowing park managers and beekeepers to act quickly in removing the Vespidae. The proposed methodology obtained an 85% accuracy in the detection of V. velutina using the Mask RCNN architecture, enabling the system to perform detection at 3 FPS. © 2020 MIR Labs.
2020
Autores
Madureira A.M.; Abraham A.; Silva C.; Antunes M.; Castillo O.; Ludwig S.;
Publicação
Advances in Intelligent Systems and Computing
Abstract
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