Research on image features extraction and classification using transformer model

Runhao Fu

doi:10.1117/12.3021595

19 February 2024 Research on image features extraction and classification using transformer model

Runhao Fu

Proceedings Volume 13063, Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023); 130631Q (2024) https://doi.org/10.1117/12.3021595
Event: Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023), 2023, Changchun, China

Abstract

At present, image processing has widely utilized in tremendous downstream applications including robotics, detection sensors and industrial products. Existing processing methods have achieved considerable accuracy towards complex images. However, existing classification concentrates on the convolution operation and ignore extraordinary information in feature space. In this work, we propose a novel classification based on the extracted features of images and utilized most advanced transformer model to identify the information from diverse images. Initially, the model extracts the features from the feature space and identify the feature information. Subsequently, the transformer model will train the classification mechanism through recognizing the feature information with the target labels. Finally, the trained model can recognize the different objectives in real-world images. From our extensive simulation and comparison analysis, we can conclude that proposed model can achieve the target classification with acceptable accuracy and reasonable training costs.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Runhao Fu "Research on image features extraction and classification using transformer model", Proc. SPIE 13063, Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023), 130631Q (19 February 2024); https://doi.org/10.1117/12.3021595

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