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Development of an Automotive Safety System for Pedestrian Detection by Fusing Information from Reversing Camera and Proximity Sensors Using Convolutional Neural Networks

Published: 06 January 2024 Publication History

Abstract

This research focuses on the use of artificial intelligence and data analysis, both images and distances, to design a model capable of detecting pedestrians in the vehicle’s reverse camera, considering different road scenes to establish a more robust algorithm. The main objective is to address road safety issues affecting vulnerable pedestrians in collisions with backward-moving vehicles.

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  1. Development of an Automotive Safety System for Pedestrian Detection by Fusing Information from Reversing Camera and Proximity Sensors Using Convolutional Neural Networks

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    CLIHC '23: Proceedings of the XI Latin American Conference on Human Computer Interaction
    October 2023
    247 pages
    ISBN:9798400716577
    DOI:10.1145/3630970
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 06 January 2024

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    Author Tags

    1. Artificial intelligence
    2. CNNs
    3. Deep learning
    4. Distances
    5. Sensors

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    Overall Acceptance Rate 14 of 42 submissions, 33%

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