| Title |
Intelligent Design and Application of LOGO Based on Regional Guidance and Enhanced Network |
| DOI |
https://doi.org/10.5573/IEIESPC.2025.14.4.431 |
| Keywords |
Regional guidance; Enhanced network; YOLOv3 detection; Logo design; Convolutional neural classification network |
| Abstract |
The intelligent design of logos has great application prospects in product analysis and product authenticity identification. To achieve more effective logo design, the Discriminatory Regional Guidance and Enhancement Network (DRGE-Net) was introduced for feature extraction and classification of images, and a Logo YOLO detection method was proposed for precise detection of image targets. It was proved that in the performance experiment of validating the logo classification method, the classification accuracy of DRGE-Net in the four best performing logo categories was above 80%, and the highest reached 92.68%. At the same time, among the four worst performing logo categories, the classification accuracy of DRGE-Net was higher than 50%, and the highest reached 60.8%. In the experiment to verify the function of the logo detection method, the Logo YOLO detection method achieved the mean average precision (mAP) values in the three major categories of clothing, food, and essential goods, with 61.58%, 56.42%, and 61.97%, respectively. The classification and detection performance of these two methods have significant advantages, providing effective technical support for the intelligent design of logos. |