Improving Fashion Attribute Classification Accuracy with Limited Labeled Data Using Transfer Learning-Reference-Cited by-同舟云学术

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Improving Fashion Attribute Classification Accuracy with Limited Labeled Data Using Transfer Learning

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)
language:
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Author:

Chen Tong¹,Noh Jiho¹,Cranfill Luke²,Morris John³,Son Junggab⁴

Affiliation:

1. Kennesaw State University,Dept. of Computer Science,Marietta,GA,USA

2. Homedepot,Dept. of Retail Media,Atlanta,GA,USA

3. Oracle,Retail Global Business Unit,Atlanta,GA,USA

4. University of Nevada, Las Vegas,Dept. of Computer Science,Las Vegas,NV,USA

Funder

Oracle

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10068862/10068777/10069704.pdf?arnumber=10069704

Reference30 articles.

1. DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations

2. ClothingNet: Cross-Domain Clothing Retrieval With Feature Fusion and Quadruplet Loss

3. Transfer Learning from Synthetic Data Applied to Soil–Root Segmentation in X-Ray Tomography Images

4. DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images

5. 2d geometric shapes dataset;anas,2020

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