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Pabelco Zambrano, F. C., Héctor Villegas, Jonathan Paillacho, Doménica Pazmiño, Miguel Realpe. (2023). UAV Remote Sensing applications and current trends in crop monitoring and diagnostics: A Systematic Literature Review. In IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) 2023, julio 4-7.
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Sara Nieto, E. M., Ricardo Villacis, Fernanda Calderon, Hector Villegas, Jonathan Paillacho and Miguel Realpe. (2023). A Practical Study on Banana (Musa spp.) Plant Counting and Coverage Percentage Using Remote Sensing and Deep Learning. In International Conference on Geospatial Information Sciences, iGISc 2023.
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Tyrone Rodríguez, A. G., Paolo Piedrahita & Miguel Realpe. (2024). Towards Birds Conservation in Dry Forest Ecosystems through Audio Recognition via Deep Learning. In In 9th International Congress on Information and Communication Technology ICICT 2024.
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Miguel Realpe, Boris X. Vintimilla, & Ljubo Vlacic. (2016). Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles. Journal of Automation and Control Engineering (JOACE), Vol. 4, pp. 430–436.
Abstract: Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset.
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