Many algorithms have been developed as a result of recent advances in machine learning to handle a variety of
challenges. In recent years, the most popular transfer learning method has allowed researchers and engineers to run
experiments with minimal computing and time resources. To tackle the challenges of classification, product identification,
product suggestion, and picture-based search, this research proposed a transfer learning strategy for Fashion image
classification based on hybrid 2D-CNN pretrained by VGG-16 and AlexNet.