รหัสดีโอไอ 10.14457/TU.the.2020.77
Title Car damage classification for car insurance company by using Colab with convolutional neural networks deep learning method
Creator Supavee Tanutammakun
Contributor Jirachai Buddhakulsomsiri, Advisor
Publisher Thammasat University
Publication Year 2020
Keyword Car classification ,Car detection ,Car damage ,Machine learning ,Car insurance
Abstract The motor insurance in Thailand has the highest market share in the non-life insurance segment which is around 60% of insurance industry. Thailand using the traditional claiming process which consuming a lot of time. However, in some country such as United State has been applied Artificial Intelligence and Machine Learning with car insurance claiming process and due to car damage dataset is provided from the insurance company in Thailand. The car damage is classified as 4 levels. The study is building the model by using Google Colab and applied Convolutional Neural Network as deep learning method. The accuracy of the model for car damage classification is 74.59%. The defuzzification is applied to predict the duration day for fixing which using for customers to planning when they have an accident. Recommendations are also discussed.
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Supavee Tanutammakun และผู้แต่งคนอื่นๆ. (2020) Car damage classification for car insurance company by using Colab with convolutional neural networks deep learning method. Thammasat University:ม.ป.ท.
Supavee Tanutammakun และผู้แต่งคนอื่นๆ. 2020. Car damage classification for car insurance company by using Colab with convolutional neural networks deep learning method. ม.ป.ท.:Thammasat University;
Supavee Tanutammakun และผู้แต่งคนอื่นๆ. Car damage classification for car insurance company by using Colab with convolutional neural networks deep learning method. ม.ป.ท.:Thammasat University, 2020. Print.