ForkNet: Overlapping Image Disentanglement for Accurate Prohibited Item Detection-Reference-Cited by-同舟云学术

ForkNet: Overlapping Image Disentanglement for Accurate Prohibited Item Detection

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Jia Tong¹^ORCID,Ma Bowen²^ORCID,Wang Hao²^ORCID,Li Mingyuan²^ORCID,Lin Shuyang²^ORCID,Chen Dongyue²^ORCID

Affiliation:

1. College of Information Science and Engineering and the Key Laboratory of Data Analysis and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China

2. College of Information Science and Engineering, Northeastern University, Shenyang, China

Funder

National Natural Science Foundation of China

National Key Research and Development Project of China

Fundamental Research Funds for the Central Universities

Major Program of National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10510166.pdf?arnumber=10510166

Reference59 articles.

1. Improving Weapon Detection in Single Energy X-Ray Images Through Pseudocoloring

2. Using Image Processing Methods to Improve the Explosive Detection Accuracy

3. Detection of cargo container loads from X-ray images

4. On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening

5. Object Recognition in Baggage Inspection Using Adaptive Sparse Representations of X-ray Images

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