... different annotators. Besides, it is particularly difficult to make image annotation for dresses with rich style variations and massive image data. To solve this problem, in this study, an automatic recognition method of multi-label images based on deep learning is proposed. Design/methodology/approach...

... machine learning models (support vector machine, decision tree), we developed a novel hybrid deep learning architecture integrating long short-term memory (LSTM) networks with convolutional neural networks (CNN). This configuration enables simultaneous temporal pattern recognition through LSTM layers...

... diverse design variations, making them suitable for evaluating the performance of the proposed process. 01 03 2025 19 08 2025 18 09 2025 © Emerald Publishing Limited 2025 Emerald Publishing Limited Licensed re-use rights only Artificial intelligence Deep learning Flat...

... recommendation engines by using cutting-edge deep learning methods. Cloth-Net is a powerful method for improving the classification accuracy of 2D and 3D clothing photos. Its core is a hybrid adversarial network coupled with a Vision Transformer architecture (Mir et al., 2020). Cloth-Net’s...

... details of the original image. However, this objective, pose two primary challenges that demand resolution: Artificial intelligence design Deep learning GAN Attribute editing Women’s blouse While the AI applications in the field of design are not fully mature yet (Cheng et al...

... The newly developed model was able to cope with the cold start problem better than other models. Social implications A hybrid recommendation system has been developed that combines the existing recommendation system with deep learning to effectively recommend fashion products considering the user's...

...Qi Xiao; Rui Wang; Hongyu Sun; Limin Wang Purpose The paper aims to build a new objective evaluation method of fabric pilling by combining an integrated image analysis technology with a deep learning algorithm. Design/methodology/approach Series of image analysis techniques were adopted. First...

.... For deep learning, two models are introduced to train the prediction model, one is a convolutional neural network joint with the baseline classifier support vector machine and the other is with a newly proposed classifier later kernel fusion. Findings The results show that the most accurate model...