Real-time Indian TSR using MDEffNet

Banhi Sanyal, Anshuman Padhy, R. Mohapatra, Ratnakar Dash
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Abstract

Traffic sign recognition (TSR) is an important aspect of Intelligent transport systems (ITS). The lack of architectures that are flexible across multiple datasets are rarely there. As such this work attempts to use an efficient Deep neural network (DNN) architecture and implement it on an Indian traffic sign dataset IRSDBv1.0. IRSDBv1.0 is the first publicly available Indian datset, to the best our knowledge. The performance of MDEffNet is studied and analyzed.
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使用mdefnet的实时印度TSR
交通标志识别(TSR)是智能交通系统的一个重要方面。很少有架构能够灵活地跨多个数据集。因此,这项工作试图使用高效的深度神经网络(DNN)架构,并在印度交通标志数据集IRSDBv1.0上实现它。据我们所知,IRSDBv1.0是第一个公开可用的印度数据集。对MDEffNet的性能进行了研究和分析。
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