Title: Research on detection technology of appearance intellectual property based on convolutional neural network

Authors: Haiyan Huang

Addresses: Computer Engineering College, Guangzhou City University of Technology, Guangzhou, Guangdong, China

Abstract: Aiming at the problem of low accuracy of traditional cigarette box appearance intellectual property detection, an appearance intellectual property detection method based on CNN-LSTM is proposed. CNN network and LSTM network are adopted to extract the spatial and temporal features of cigarette boxes respectively, and the fusion processing is carried out. Then, the multi-branch parallel appearance segmentation model is used to segment images. The results show that the detection accuracy of the proposed model is 99.81%, which is 4.21%, 8.98% and 10.96% higher than that of Inception, ResNet and MobileNet networks, respectively. This shows that the method can improve the accuracy of intellectual property detection of cigarette boxes.

Keywords: convolutional neural network; LSTM; cigarette boxes; intellectual property; appearance detection.

DOI: 10.1504/IJWMC.2024.138861

International Journal of Wireless and Mobile Computing, 2024 Vol.26 No.4, pp.361 - 373

Received: 28 Aug 2023
Accepted: 19 Dec 2023
Published online: 31 May 2024 *

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