Research on image features extraction based on graph convolutional network

Yingyun Zheng

doi:10.1117/12.3004089

11 October 2023 Research on image features extraction based on graph convolutional network

Yingyun Zheng

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128002F (2023) https://doi.org/10.1117/12.3004089
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

With the continuous development and progress of information technology and image sensors, the amount of data contained in digital images is increased. Therefore, the image feature extraction and downstream applications have begun to receive widespread attention by computer vision field. However, the majority of existing contributions are concentrated on the utilization of machine learning models and ignore the graph convolution theory can also be utilized to extract the small differences features from input images. In this paper, we utilize the graph convolution model to dispose the issue that small differences between classes make sample differentiation difficult in the process of feature extraction with optimization loss functions in the feature space. From our experimental results, we can conclude that our proposed model can achieve the image feature extraction and validate the identification accuracy reaching to approximately 95% for image classification task with reasonable system costs.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yingyun Zheng "Research on image features extraction based on graph convolutional network", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128002F (11 October 2023); https://doi.org/10.1117/12.3004089

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KEYWORDS

Feature extraction

Machine learning

Image processing

Image segmentation

Convolution

Computer vision technology

Data modeling

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