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Emo-AEN: A Lightweight Network for Brand Image Design Based on Aesthetic Evaluation

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Abstract

In the aesthetic evaluation of multimedia data, brand image design is closely intertwined with image aesthetics. Although previous researchers have made significant contributions in this field, the intrinsic relationship between the two has not been fully explored. To address this issue, this paper proposes Emo-AEN: a lightweight image aesthetic assessment method that combines brand image design with attention mechanisms. This method takes into account the aesthetic elements involved in the process of brand image design. The network first performs internal fusion operations to obtain fused features of brand image and image aesthetics. Then, through self-attention mechanisms, it thoroughly explores these fused features. This method not only enhances the expressive power of brand image design but also uncovers the intrinsic relationship between brand image design and image aesthetics,and its lightweight model architecture can be deployed in resource-constrained device environments.

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No datasets were generated or analysed during the current study.

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Authors and Affiliations

  1. School of Communication, Tianjin Foreign Studies University, Machang, 300204, Tianjin, China

    Honglei Cheng

  2. School of Electrical and Information Engineering, Tianjin University, Weijin Road, Tianjin, 300072, Tianjin, China

    Guipeng Lan & Shuai Xiao

  3. School of future technology, Tianjin University, Weijin Road, Tianjin, 300072, Tianjin, China

    Haorui Yi

Authors
  1. Honglei Cheng
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  2. Haorui Yi
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  3. Guipeng Lan
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  4. Shuai Xiao
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Contributions

The author contributions for this manusc are as follows: Honglei Cheng: Conceived the research idea, designed the experiments, and analyzed the data, drafted the manuscript Haorui Yi: Implemented the algorithms, and conducted simulations, drafted the manuscript Guipeng Lan: Conducted the literature review, collected the data, and performed statistical analysis. Shuai Xiao: Drafted the manuscript, prepared figures and tables, and revised the manuscript.

Corresponding author

Correspondence to Guipeng Lan.

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Cheng, H., Yi, H., Lan, G. et al. Emo-AEN: A Lightweight Network for Brand Image Design Based on Aesthetic Evaluation. Mobile Netw Appl (2024). https://doi.org/10.1007/s11036-024-02314-y

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