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Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network

文献类型：期刊论文

作者Yuan, Jian-ye2; Nan, Xin-yuan2; Li, Cheng-rong1; Sun, Le-le3
刊名MATHEMATICAL PROBLEMS IN ENGINEERING
出版日期2020-11-30
卷号2020页码:6
ISSN号1024-123X
DOI10.1155/2020/5795976
通讯作者Nan, Xin-yuan(yuanxianshengo@163.com)
英文摘要Considering that the garbage classification is urgent, a 23-layer convolutional neural network (CNN) model is designed in this paper, with the emphasis on the real-time garbage classification, to solve the low accuracy of garbage classification and recycling and difficulty in manual recycling. Firstly, the depthwise separable convolution was used to reduce the Params of the model. Then, the attention mechanism was used to improve the accuracy of the garbage classification model. Finally, the model fine-tuning method was used to further improve the performance of the garbage classification model. Besides, we compared the model with classic image classification models including AlexNet, VGG16, and ResNet18 and lightweight classification models including MobileNetV2 and SuffleNetV2 and found that the model GAF_dense has a higher accuracy rate, fewer Params, and FLOPs. To further check the performance of the model, we tested the CIFAR-10 data set and found the accuracy rates of the model (GAF_dense) are 0.018 and 0.03 higher than ResNet18 and SufflenetV2, respectively. In the ImageNet data set, the accuracy rates of the model (GAF_dense) are 0.225 and 0.146 higher than Resnet18 and SufflenetV2, respectively. Therefore, the garbage classification model proposed in this paper is suitable for garbage classification and other classification tasks to protect the ecological environment, which can be applied to classification tasks such as environmental science, children's education, and environmental protection.
WOS研究方向Engineering ; Mathematics
语种英语
WOS记录号WOS:000599836000005
出版者HINDAWI LTD
源URL[http://ir.ia.ac.cn/handle/173211/42776]  
专题自动化研究所_智能制造技术与系统研究中心
通讯作者Nan, Xin-yuan
作者单位1.Chinese Acad Sci, Inst Automat, Intelligent Mfg Technol & Syst Res Ctr, Beijing 100190, Peoples R China
2.Xinjiang Univ, Sch Elect Engn, Urumqi 830047, Peoples R China
3.Shandong Huayu Univ Technol, Sch Elect Engn, Dezhou 253034, Peoples R China
推荐引用方式
GB/T 7714		 Yuan, Jian-ye,Nan, Xin-yuan,Li, Cheng-rong,et al. Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2020,2020:6.
APA Yuan, Jian-ye,Nan, Xin-yuan,Li, Cheng-rong,&Sun, Le-le.(2020).Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network.MATHEMATICAL PROBLEMS IN ENGINEERING,2020,6.
MLA Yuan, Jian-ye,et al."Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network".MATHEMATICAL PROBLEMS IN ENGINEERING 2020(2020):6.

入库方式： OAI收割

来源：自动化研究所

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