TY - GEN
T1 - Ship detection and recognition based on multi-physical fields
AU - Li, Yongqiang
AU - Li, Tie
AU - Yan, Wei
AU - Cui, Dong
AU - Zhao, Qi
AU - Ding, Mingli
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/5
Y1 - 2016/12/5
N2 - The detection and identification of the kinds of ships, i.e., warship or merchant ship, is of great interest for military use. Ships are usually detected and recognized based on ship physical fields, and the commonly used ship physical fields include sound field, magnetic field, hydraulic pressure field, electric field, gravity field, etc, which all contain plenty of discriminative information. However, the existing ship identification methods are usually based on single ship physical field, which will limit the model performance. In this work, we proposed a ship recognition method based on combination of multi-physical fields, i.e., sound field and magnetic field. To the best of the authors' knowledge, this is the first work to recognize ships based on multi-physical fields. We fuse features extracted from multi-physical fields by Principal Component Analysis (PCA), which is then fed to Support Vector Machine (SVM) to realize the recognition of ship. Plenty of experiments demonstrate the effectiveness of the proposed method.
AB - The detection and identification of the kinds of ships, i.e., warship or merchant ship, is of great interest for military use. Ships are usually detected and recognized based on ship physical fields, and the commonly used ship physical fields include sound field, magnetic field, hydraulic pressure field, electric field, gravity field, etc, which all contain plenty of discriminative information. However, the existing ship identification methods are usually based on single ship physical field, which will limit the model performance. In this work, we proposed a ship recognition method based on combination of multi-physical fields, i.e., sound field and magnetic field. To the best of the authors' knowledge, this is the first work to recognize ships based on multi-physical fields. We fuse features extracted from multi-physical fields by Principal Component Analysis (PCA), which is then fed to Support Vector Machine (SVM) to realize the recognition of ship. Plenty of experiments demonstrate the effectiveness of the proposed method.
KW - Magnetic field
KW - SVM
KW - Ship physical fields
KW - Ship recognition
KW - Sound field
UR - https://www.scopus.com/pages/publications/85010304548
U2 - 10.1109/IMCCC.2016.195
DO - 10.1109/IMCCC.2016.195
M3 - 会议稿件
AN - SCOPUS:85010304548
T3 - Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016
SP - 19
EP - 23
BT - Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016
A2 - Li, Junbao
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016
Y2 - 21 July 2016 through 23 July 2016
ER -