{"title":"深度卷积神经网络在汽车图像分类中的比较研究","authors":"Phuriwat Rasameekunwit, Wutthichai Puangmanee","doi":"10.1109/RI2C56397.2022.9910270","DOIUrl":null,"url":null,"abstract":"This paper aims to present the result of a comparative study of Deep Convolutional Neural Networks (CNN) using the AlexNet architecture to use the car image classification of a small dataset. We have proposed the experiment result from a comparative study dropout value using Cuckoo Search (CS), of the optimization techniques for a small data set solving problem of overfitting. The car images for the experiment are different in color, size, and position. As a result, the training time average of $\\sim 59.16$ minutes, and the model accuracy of 91.41%.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comparative Study of Deep Convolutional Neural Networks for Car Image Classification\",\"authors\":\"Phuriwat Rasameekunwit, Wutthichai Puangmanee\",\"doi\":\"10.1109/RI2C56397.2022.9910270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims to present the result of a comparative study of Deep Convolutional Neural Networks (CNN) using the AlexNet architecture to use the car image classification of a small dataset. We have proposed the experiment result from a comparative study dropout value using Cuckoo Search (CS), of the optimization techniques for a small data set solving problem of overfitting. The car images for the experiment are different in color, size, and position. As a result, the training time average of $\\\\sim 59.16$ minutes, and the model accuracy of 91.41%.\",\"PeriodicalId\":403083,\"journal\":{\"name\":\"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RI2C56397.2022.9910270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RI2C56397.2022.9910270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comparative Study of Deep Convolutional Neural Networks for Car Image Classification
This paper aims to present the result of a comparative study of Deep Convolutional Neural Networks (CNN) using the AlexNet architecture to use the car image classification of a small dataset. We have proposed the experiment result from a comparative study dropout value using Cuckoo Search (CS), of the optimization techniques for a small data set solving problem of overfitting. The car images for the experiment are different in color, size, and position. As a result, the training time average of $\sim 59.16$ minutes, and the model accuracy of 91.41%.
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