Traffic Sign Recognition Based on Bayesian Angular Margin Loss for an Autonomous Vehicle Article Swipe

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Taehyeon Kim , Se-Ho Park , Kyoungtaek Lee ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.3390/electronics12143073

Traffic sign recognition is a pivotal technology in the advancement of autonomous vehicles as it is critical for adhering to country- or region-specific traffic regulations. Defined as an image classification problem in computer vision, traffic sign recognition is a technique that determines the class of a given traffic sign from input data processed by a neural network. Although image classification has been considered a relatively manageable task with the advent of neural networks, traffic sign classification presents its own unique set of challenges due to the similar visual features inherent in traffic signs. This can make designing a softmax-based classifier problematic. To address this challenge, this paper presents a novel traffic sign recognition model that employs angular margin loss. This model optimizes the necessary hyperparameters for the angular margin loss via Bayesian optimization, thereby maximizing the effectiveness of the loss and achieving a high level of classification performance. This paper showcases the impressive performance of the proposed method through experimental results on benchmark datasets for traffic sign classification.

Related Topics

Traffic Sign

Softmax Function

Computer Science

Artificial Intelligence

Benchmark (Surveying)

Mathematical Analysis

Concepts

Traffic sign Traffic sign recognition Softmax function Computer science Artificial intelligence Classifier (UML) Margin (machine learning) Benchmark (surveying) Hyperparameter Bayesian probability Artificial neural network Machine learning Feature extraction Pattern recognition (psychology) Sign (mathematics) Data mining Geodesy Geography Mathematics Mathematical analysis

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Type: article
Language: en
Landing Page: https://doi.org/10.3390/electronics12143073
PDF: https://www.mdpi.com/2079-9292/12/14/3073/pdf?version=1689327182
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Cited By: 4
References: 43
Related Works: 10
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DOI: https://doi.org/10.3390/electronics12143073

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Title: Traffic Sign Recognition Based on Bayesian Angular Margin Loss for an Autonomous Vehicle

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Language: en

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Publication year: 2023

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Publication date: 2023-07-14

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Authors: Taehyeon Kim, Se-Ho Park, Kyoungtaek Lee

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Landing page: https://doi.org/10.3390/electronics12143073

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Concepts: Traffic sign, Traffic sign recognition, Softmax function, Computer science, Artificial intelligence, Classifier (UML), Margin (machine learning), Benchmark (surveying), Hyperparameter, Bayesian probability, Artificial neural network, Machine learning, Feature extraction, Pattern recognition (psychology), Sign (mathematics), Data mining, Geodesy, Geography, Mathematics, Mathematical analysis

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Cited by: 4

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Citations by year (recent): 2025: 2, 2024: 2

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