HIGHLIGHTS
- who: Yeonsik Jo and collaborators from the School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Department of Industrial Engineering, Chonnam National University, Yongbong-ro, Buk-gu have published the research: Flexible Fashion Product Retrieval Using Multimodality-Based Deep Learning, in the Journal: (JOURNAL)
- what: A quantitative analysis was conducted to evaluate based on these data by applying and comparing the concatenation, pointwise (or elementwise) sum, and pointwise product methods. The authors propose a flexible fashion product search method that employs multimodality-based deep learning while utilizing the most widely-used . . .
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