A new image classification method using CNN transfer learning and web data augmentation
作者：
Highlights：
• We do image classification on training data limited dataset with deep learning.
• Transfer learning is employed to overcome the serious over-fitting.
• Web data augmentation is developed to improve the classification performance.
• Bayesian optimization is employed to facilitate the hyper-parameter search.
摘要
•We do image classification on training data limited dataset with deep learning.•Transfer learning is employed to overcome the serious over-fitting.•Web data augmentation is developed to improve the classification performance.•Bayesian optimization is employed to facilitate the hyper-parameter search.
论文关键词：Feature transferring,Data augmentation,Convolutional neural network,Feature representation,Parameter fine-tuning,Bayesian optimization
论文评审过程：Received 23 February 2017, Revised 26 October 2017, Accepted 11 November 2017, Available online 13 November 2017, Version of Record 20 November 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.028
