Author(s)

Jin Lu, Xiaoting Wan*

Affiliation(s)

Guangdong Key Laboratory of Big Data Intelligence for Vocational Education, Shenzhen Polytechnic, Shenzhen 518055, Guangdong, China.

Corresponding Author

Xiaoting Wan, email: wanxt@szpt.edu.cn

ABSTRACT

The research progress of image classification based on deep learning and data-driven is done by many researchers. The main aim of the researcher is to improve the accuracy of the classifier which can be used as a tool in various applications like security, medical, etc. There are many other uses for this technology that are not yet known to us. In this article we will discuss about some methods to improve our results with deep learning and data-driven techniques.Deep learning is a subfield of machine learning that has been used to solve many problems in computer vision and natural language processing. In this paper, we propose an image classification algorithm based on deep convolutional neural network (DCNN) and data-driven feature selection method. The DCNNs are trained with the help of transfer learning from existing state-of-the-art deep networks such as Alexnet, GoogLeNet, CNN, SVM, etc., which have been successfully applied for object detection.

KEYWORDS

Image Classification, Deep Learning, Data Driven, Overview.

CITE THIS PAPER

Lu Jin, Wan Xiaoting. Research progress of image classification based on deep learning and data driven. Journal of Computer Science and Electrical Engineering. 2022, 4(1): 8-13.

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