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AniDriveQA: a VQA dataset for driving scenes with animal presence. [PDF]

Front Robot AI
Wang R, Wang R, Hu H, Yu H.
europepmc   +1 more source

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Traffic Sign Classification Using ODENet

2021
In the family of deep neural network models, deeper the model is, the longer it takes to predict and larger the memory space it utilizes. It is very much likely that use-cases have constraints to be respected, especially on embedded devices, i.e, low powered, memory-constrained systems.
Yaratapalli Nitheesh Chandra Sainath, Reethesh Venkataraman, Abhishek Dinesan, Ashni Manish Bhagvandas, Padmamala Sriram   +4 more
openaire   +1 more source

Multiple-dataset traffic sign classification with OneCNN

2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 2015
We take a look at current state of traffic sign classification discussing what makes it a specific problem of visual object classification. With impressive state-of-the- art results it is easy to forget that the domain extends beyond annotated datasets and overlook the problems that must be faced before we can start training classifiers.
Jurišić, Fran, Filković, Ivan, Kalafatić, Zoran   +2 more
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Classification of Traffic Signs

2017
This chapter started with reviewing related work in the field of traffic sign classification. Then, it explained the necessity of splitting data and some of methods for splitting data into training, validation, and test sets. A network should be constantly assessed during training in order to diagnose it if it is necessary.
Hamed Habibi Aghdam, Elnaz Jahani Heravi
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Shape Classification for Traffic Sign Recognition

IFAC Proceedings Volumes, 1993
Abstract A traffic sign detection and recognition approach is presented in this paper. This project is a part of the European research project PROMETHEUS(PROgraM for a European Traffic with Highest Efficiency and Unprecedented Safety) and is being developed by DAIMLER BENZ in collaboration with various university labs.
B. Besserer, S. Estable, B. Ulmer, D. Reichardt   +3 more
openaire   +1 more source

Thai traffic sign classification system

2023
Nowadays, driving assistance technology is continuously developed to serve a comfortable and safe driving experience for the driver. The traffic sign is an important feature to improve the ability of this technology. However, in general, the traffic sign has various structures and details in each specific country for a clearly understanding purpose ...
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Towards real-time traffic sign detection and classification

17th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2014
Traffic sign recognition plays an important role in driver assistant systems and intelligent autonomous vehicles. Its real-time performance is highly desirable in addition to its recognition performance. This paper aims to deal with real-time traffic sign recognition, i.e., localizing what type of traffic sign appears in which area of an input image at
Yi Yang, Hengliang Luo, Huarong Xu, Fuchao Wu   +3 more
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Study on traffic sign classification for assessing sign comprehension

Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), 2011
Previous studies analyzed the relationship between drivers' personal characteristics and their comprehension of traffic signs directly, but neglected to test and control the influence of small class of traffic signs themselves. This error might cause the distortion of research results.
null Rong Jian, null Guo Ruili, null Wei Zhonghua, null Wu Yongyan   +3 more
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Real-Time Classification of Traffic Signs

Real-Time Imaging, 2000
A challenging real-time imaging problem is classifying video traffic signs in background clutter under rotation, scale, and translation invariant conditions. Normalized Gabor Wavelet Transform features from multi-resolution filters were originally biologically-based; however, optimized features proved more effective.
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Traffic sign classification network using inception module

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), 2019
With the rapid development of the automobile industry, the demand for autonomous driving becomes more and more urgent, and the traffic sign recognition technology in autonomous driving is an indispensable technology. This paper proposes a GoogLeNet based convolutional neural network for traffic signs.
Zhao Dongfang, Kang Wenjing, Li Tao, Liu Gongliang   +3 more
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