针对服装图像分类模型体积较大, 缺少细分类的问题, 提出基于改进ShuffleNet v1
的服装图像分类算法. 该算法以ShuffleNet v1 为基础, 通过优化模块的堆叠次数和网络层通道数 …

针对传统的服装图像分类方法效率低, 准确度不高等缺点, 提出了一种基于VGG16
和迁移学习的服装图像分类方法, 主要采取预训练的VGG16 网络模型, 提供了更好的模型初始化 …

In order to solve the problem of low efficiency of clothing pattern classification, a method
based on Inception v3 algorithm and transfer learning technology to classify blouse patterns …

摘要传统的服装分类方法主要是提取图像的颜色, 纹理, 边缘等特征, 过程繁琐且分类精度较低.
为了提高服装图像的分类性能和时效性, 提出一种基于迁移学习的卷积神经网络服装图像分类 …

In recent years, with the development of the Internet economy, compared with offline sales of
clothing, online shopping has broken the time and geographical restrictions, and has …

To ameliorate the precision of clothing image classification, we proposed a clothing image
classification method via the DenseNet201 network based on transfer learning and the …

To address the problems that existing garment classification effects are greatly affected by
background noise and that network features are not highly expressive. A multi-scale deep …

Image recognition and classification is a significant research topic in computational vision
and widely used computer technology. The methods often used in image classification and …

Automatic clothing classification with deep learning models becomes an inevitable trend in
the era of artificial intelligence. Clothing classification methods using conventional …

The transformation of fashion through online platforms has spurred a need for high-quality
clothing search engines, facilitating seamless product discovery for global consumers …