Paper
5 July 2024 Research on image features extraction and classification based on transformer model
Haitang Lin, Zhendong Li, Chengjun Wen, Guohong Liu, Fang Ding
Author Affiliations +
Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131842F (2024) https://doi.org/10.1117/12.3032935
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia
Abstract
With the rapid development of computer vision and machine learning technology, the extraction and classification of image features has become one of the core tasks in these fields. Traditionally, classification tasks primarily relay on convolution neural networks, which are very effective at capturing local features of images. However, there are limitations when dealing with the global and complex relationships of images. In this work, we propose a novel transformer model to dispose the features extraction and classification task. Initially, the model explores how to apply the transformer model to the extraction of image features, including methods for segmentation and encoding of images. Additionally, the model can identify and understand the different parts and attributes of the image, which is essential for subsequent classification tasks. Subsequently, the model uses the extracted features to distinguish between different classes of images. The study demonstrates the classification performance of the model in a variety of complex scenarios, including those that require a detailed understanding of image content. From our extensive experiments analysis, we can conclude that our proposed model can achieve the features extraction and outperform classification accuracy with existing models.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Haitang Lin, Zhendong Li, Chengjun Wen, Guohong Liu, and Fang Ding "Research on image features extraction and classification based on transformer model", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131842F (5 July 2024); https://doi.org/10.1117/12.3032935
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KEYWORDS
Feature extraction

Image classification

Transformers

Image processing

Data modeling

Deep learning

Visual process modeling

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