基于Faster R-CNN与YOLOv8多模型融合的电子商务图像分类与识别

E-Commerce Image Classification and Recognition Based on Faster R-CNN and YOLOv8 Multi Model Fusion

摘要: 随着电子商务的快速发展，图像分类与识别技术在商品自动分类、图像检索等方面扮演着越来越重要的角色。为了提高图像识别的准确性和实时性，本文提出了一种基于Faster R-CNN与YOLOv8多模型融合的方法，并结合置信度特征融合与高级分类器进行电子商务图像的分类与识别。

Abstract: With the rapid development of e-commerce, image classification and recognition technology plays an increasingly important role in automatic product classification, image retrieval, and other aspects. In order to improve the accuracy and real-time performance of image recognition, this paper proposes a method based on Faster R-CNN and YOLOv8 multi model fusion, and combines confidence feature fusion with advanced classifiers for e-commerce image classification and recognition.