2020 VOL.3 Feb No.1

• Title: Research on Image Classification Algorithm Based on Improved AlexNet in Cloud Computing Environment
• Name: Byung-Joo Pu
• Company: Korea Advanced Institute of Science and Technology
• Abstract:

  In the cloud computing environment, traditional classification algorithms often ignore the feature relationships between images, which causes problems such as unstable classification processes and poor accuracy of classification results, which can not achieve the desired classification effect. To this end, an image classification algorithm based on improved AlexNet is proposed and designed. After pre-processing such as normalization, averaging, and standardization of the collected images, convolutional nerves are introduced to perform feature training on standard images. On this basis, an image classification algorithm model based on improved AlexNet is established, and the high-level semantic features of the image are extracted through the optimized training of the classification model to realize the image classification calculation process. Experiments show that the improved AlexNet image classification algorithm improves the accuracy and stability of image classification, and has good effectiveness and robustness.

• Keyword: Cloud Computing Environment; Improved Alexnet Model; Convolutional Neural Network; Image Classification
• DOI: 10.12250/jpciams2020010114
• Citation form: Byung-Joo Pu.Research on Image Classification Algorithm Based on Improved AlexNet in Cloud Computing Environment[J]. Computer Informatization and Mechanical System, 2020, vol. 3, pp. 140-146.

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