Toward Dual-View X-Ray Baggage Inspection: A Large-Scale Benchmark and Adaptive Hierarchical Cross Refinement for Prohibited Item Discovery-Reference-Cited by-同舟云学术

Toward Dual-View X-Ray Baggage Inspection: A Large-Scale Benchmark and Adaptive Hierarchical Cross Refinement for Prohibited Item Discovery

Published:2024 Issue: Volume:19 Page:3866-3878
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Ma Bowen¹^ORCID,Jia Tong²^ORCID,Li Mingyuan¹,Wu Songsheng¹,Wang Hao¹^ORCID,Chen Dongyue¹^ORCID

Affiliation:

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

2. Key Laboratory of Data Analysis and Optimization for Smart Industry, Ministry of Education, and the 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

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/ielx7/10206/10319981/10458082.pdf?arnumber=10458082

Reference51 articles.

1. Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery

2. “Unexpected Item in the Bagging Area”: Anomaly Detection in X-Ray Security Images

3. Detecting Overlapped Objects in X-Ray Security Imagery by a Label-Aware Mechanism

4. Automated Segmentation of Prohibited Items in X-ray Baggage Images Using Dense De-overlap Attention Snake

5. SIXray: A Large-Scale Security Inspection X-Ray Benchmark for Prohibited Item Discovery in Overlapping Images

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