Multi-neural Networks Object Identification



 Journal of Electrical Engineering
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Title: Multi-neural Networks Object Identification
Abstract: This paper presents an Android prototype called HOLOTECH, a system to help blind people to understand obstacles in the environment. The goal of this paper is the analysis of different techniques and procedures to perform a fast and lightweight model able to detect obstacles in this context. The predictions and analysis are statistically evaluated, and results are used in order to improve the inference results. The model keeps working using low precision images drifted from an Android cell phone supported with ultrasonic sensors. Images are pre-processed on the fly, using multiple neural networks in conjunction with other heuristics, to infer obstacles and their displacement. Results indicate that it is possible to improve the prediction rate and at the same time to reduce extra processing load. ? 2021, Springer Nature Switzerland AG.
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