Zero-shot image classification based on attribute word response

Chenyu Wu; Jianxun Hong

doi:10.1117/12.3004637

20 October 2023 Zero-shot image classification based on attribute word response

Chenyu Wu, Jianxun Hong

Proceedings Volume 12916, Third International Conference on Signal Image Processing and Communication (ICSIPC 2023); 129160H (2023) https://doi.org/10.1117/12.3004637
Event: Third International Conference on Signal Image Processing and Communication (ICSIPC 2023), 2023, Kunming, China

Abstract

In practical industrial production, it is often difficult for machine learning to obtain sufficient image features due to the need for confidentiality or the scarcity of samples themselves. Therefore, this article conducts in-depth research in the field of Zero-shot Learning (ZSL). The key assignment of ZSL is how to infer latent semantic expertise between visible aspects of seen lessons and textual attribute features, so as to reap know-how switch to invisible classes. This article proposes an advanced algorithm in ZSL, which realizes the classification and recognition of unknown images by establishing a mapping relationship between local semantic attributes of text and images. The research in this article mainly includes the following aspects. Different from the traditional way of marking significant features manually, multiple different feature attributes are jointly used to guide the learning of global and local features of images. First, by using a text encoder and an image encoder, the text attribute words are encoded and embedded into the visual space, aligning the information of the two modalities in one dimension. Then, through self-attention mechanism, the semantic connection between attribute text and local visual information is established. Finally, through the classification module, the joint prediction attribute vector of global and local features is established, and the cosine similarity is used to predict the relative distribution of attributes between and within classes, thereby improving the generalization of prior knowledge in visible classes to invisible classes.

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

Citation Download Citation

Chenyu Wu and Jianxun Hong "Zero-shot image classification based on attribute word response", Proc. SPIE 12916, Third International Conference on Signal Image Processing and Communication (ICSIPC 2023), 129160H (20 October 2023); https://doi.org/10.1117/12.3004637

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KEYWORDS

Visualization

Semantics

Machine learning

Classification systems

Image classification

Information visualization

Feature extraction

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