Abstract
Due to the subjective characteristics and rapid change of fashion style, it is relatively hard to predefine the style feature in style classification systems. In this paper we present a cognitive characteristics based clothing style autonomous development model. By the addition of special domain related information to the classic itti visual attention model, we achieve the multi-object attention model of the clothing style. And based on this we implemented the autonomous development of clothing style recognition by Multi-Layer In-place Learning Network (MILN in short). Experiments prove the feasibility and effectiveness of our model.
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Li, J., Zhong, X. (2019). Cognitive Characteristics Based Autonomous Development of Clothing Style. In: Wong, W. (eds) Artificial Intelligence on Fashion and Textiles. AITA 2018. Advances in Intelligent Systems and Computing, vol 849. Springer, Cham. https://doi.org/10.1007/978-3-319-99695-0_11
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DOI: https://doi.org/10.1007/978-3-319-99695-0_11
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