Semi-supervised Labeling Model Based on Gaussian Mixture in the Context of E-commerce Price Fraud-Reference-Cited by-同舟云学术

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Semi-supervised Labeling Model Based on Gaussian Mixture in the Context of E-commerce Price Fraud

Published:2022-09-25 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Robotics and Computer Vision (ICRCV)
language:
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Author:

Wang Jing¹,Liu Jun¹,Xia Zhiwei¹,Chen Peng²,Li Xin²,Chen Xiao²

Affiliation:

1. Wuhan Institute of Technology,Wuhan,China,430205

2. Hubei Electronic Information Product Quality Supervision & Inspection Institute,Wuhan,China,430205

Funder

Innovation Fund

Ministry of Education

Science and Technology Development Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9953195/9953171/09953227.pdf?arnumber=9953227

Reference18 articles.

1. Semi-Automated Data Labeling for Activity Recognition in Pervasive Healthcare

2. Interactive Curation of Datasets for Training and Refining Generative Models

3. CDBN: Crow Deep Belief Network Based on Scattering and AAM Features for Age Estimation [J];shejul;Journal of Signal Processing Systems,2020

4. Futures price prediction modeling and decision-making based on DBN deep learning

5. Prediction of Mechanical Properties of Hot Rolled Strip Based on DBN and Composite Quantile Regression

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Multi-Modal Profiling Fraud-Detection System for Capturing Suspicious Airline Ticket Activities;Applied Sciences;2023-12-09

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