• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid

References

1 
S. J. Lim, J. Choi, J. Lee, J. Y. Ahn, K. Moon, Feb 2019, Effect of Providing Detection Information on Improving Signal Detection Performance: Applying Simulated Baggage Screening Program, The Korean Soiciety of Safety, Vol. 34, No. 1, pp. 82-89DOI
2 
Hofer, Franziska, Hardmeier Diana, Schwaninger Adrian, 2006, Increasing airport security using the X-ray ORT as effec- tive pre-employment assessment toolGoogle Search
3 
Hardmeier, Diana, Hofer Franziska, Schwaninger Adrian, 2006, Increased detection performance in airport security screening using the X-Ray ORT as pre-employment assessment tool, Second international conference on research in air transportationGoogle Search
4 
Hardmeier, Diana, Hofer Franziska, Schwaninger Adrian, 2006, The role of recurrent CBT for increasing aviation security screeners’ visual knowledge and abilities needed in x-ray screening, The 4th International Aviation Security Tech- nology SymposiumGoogle Search
5 
H. S. Shin, K. E. Yoo, 2005, A Study on Weight of the Factors for Improvement of Air Passenger Security Screening Performance and Service, Journal of the Korean Society for Aviation and Aeronautics, Vol. 13, No. 4, pp. 29-42Google Search
6 
J. W Hong, J. H Oh, H. K Lee, 04012019, smart Airport and Next Heneration Security Screening Technology, ETRI, Vol. 34, No. 2, pp. 73-82DOI
7 
Korea Airport Corporation, Press release, https://www.airport.co.kr/Google Search
8 
LeCun, Yann, Bengio Yoshua, Hinton Geoffrey, 2015, Deep learning, nature, Vol. 521, No. 7553, pp. 436-444Google Search
9 
Baştan, Muhammet, Reza Yousefi Mohammad, M. Breuel Thomas, 2011, Visual words on baggage X-ray images, International Conference on Computer Analysis of Images and Patterns. Springer, Berlin, HeidelbergDOI
10 
Jain, Kumar Deepak, 2019, An evaluation of deep learning based object detection strategies for threat object detection in baggage security imagery, Pattern Recognition Letters 120, pp. 112-119DOI
11 
Akçay, Samet, 2016, Transfer learning using convolutional neural networks for object classification within x-ray baggage security imagery, 2016, IEEE International Conference on Image Processing (ICIP). IEEEDOI
12 
S. Cao, Y. Liu, W. Song, Z. Cui, X. Lv, J. Wan, 2019, Toward Human-in-the-Loop Prohibited Item Detection in X-ray Baggage Images, 2019 Chinese Automation Congress (CAC), Hangzhou, China, pp. 4360-4364DOI
13 
Y. LeCun, Y. Bengio, G. Hinton, 2015, Deep learning, nature, Vol. 521, pp. 436-444Google Search
14 
Szegedy Christian, Vanhoucke Vincent, Ioffe Sergey, Shlens Jon, Wojna Zbigniew, 2016, Rethinking the Inception Archi- tecture for Computer Vision, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2818-2826Google Search
15 
Chollet Francois, 2017, Xception: Deep Learning With Depthwise Separable Convolutions, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1251-1258Google Search
16 
AI Open Innovation Hub, http://www.aihub.or.kr/Google Search