Lee, H.J.[Hsi-Jian],
Huang, L.F.[Lung-Fa],
Chen, Z.[Zen],
Multi-frame ship detection and tracking in an infrared image sequence,
PR(23), No. 7, 1990, pp. 785-798.
Elsevier DOI
0401
BibRef
Musman, S.,
Kerr, D.,
Bachmann, C.,
Automatic Recognition of ISAR Ship Images,
AeroSys(32), No. 4, October 1996, pp. 1392-1404.
9611
BibRef
Maki, A.[Atsuto],
Fukui, K.[Kazuhiro],
Ship identification in sequential ISAR imagery,
MVA(15), No. 3, July 2004, pp. 149-155.
Springer DOI
0407
BibRef
Margarit, G.,
Mallorqui, J.J.,
Fortuny-Guasch, J.,
Lopez-Martinez, C.,
Exploitation of Ship Scattering in Polarimetric SAR for an Improved
Classification Under High Clutter Conditions,
GeoRS(47), No. 4, April 2009, pp. 1224-1235.
IEEE DOI
0903
BibRef
Margarit, G.,
Tabasco, A.,
Ship Classification in Single-Pol SAR Images Based on Fuzzy Logic,
GeoRS(49), No. 8, August 2011, pp. 3129-3138.
IEEE DOI
1108
BibRef
Earlier:
Correction:
GeoRS(51), No. 5, May 2013, pp. 3201.
IEEE DOI
1305
BibRef
Margarit, G.,
Barba Milanés, J.,
Tabasco, A.,
Operational Ship Monitoring System Based on Synthetic Aperture Radar
Processing,
RS(1), No. 3, September 2009, pp. 375-392.
DOI Link
1203
BibRef
Wang, Y.,
Liu, H.,
A Hierarchical Ship Detection Scheme for High-Resolution SAR Images,
GeoRS(50), No. 10, October 2012, pp. 4173-4184.
IEEE DOI
1210
BibRef
Zhu, C.,
Zhou, H.,
Wang, R.,
Guo, J.,
A Novel Hierarchical Method of Ship Detection from Spaceborne Optical
Image Based on Shape and Texture Features,
GeoRS(48), No. 9, September 2010, pp. 3446-3456.
IEEE DOI
1008
BibRef
Liu, C.,
Gierull, C.H.,
A New Application for PolSAR Imagery in the Field of Moving Target
Indication/Ship Detection,
GeoRS(45), No. 11, November 2007, pp. 3426-3436.
IEEE DOI
0709
BibRef
Brusch, S.,
Lehner, S.,
Fritz, T.,
Soccorsi, M.,
Soloviev, A.,
van Schie, B.,
Ship Surveillance With TerraSAR-X,
GeoRS(49), No. 3, March 2011, pp. 1092-1103.
IEEE DOI
1103
BibRef
Wang, X.L.[Xiao-Long],
Chen, C.X.[Cui-Xia],
An Automatic Ship Detection Method Based on Local Gray-Level Gathering
Characteristics in SAR Imagery,
ELCVIA(12), No. 1, 2013, pp. xx-yy.
WWW Link.
1306
BibRef
Velotto, D.,
Soccorsi, M.,
Lehner, S.,
Azimuth Ambiguities Removal for Ship Detection Using Full
Polarimetric X-Band SAR Data,
GeoRS(52), No. 1, January 2014, pp. 76-88.
IEEE DOI
1402
marine radar
BibRef
Hu, C.[Canbin],
Ferro-Famil, L.[Laurent],
Kuang, G.Y.[Gang-Yao],
Ship Discrimination Using Polarimetric SAR Data and Coherent
Time-Frequency Analysis,
RS(5), No. 12, 2013, pp. 6899-6920.
DOI Link
1412
BibRef
Atteia, G.E.,
Collins, M.J.[Michael J.],
On the use of compact polarimetry SAR for ship detection,
PandRS(80), No. 1, June 2013, pp. 1-9.
Elsevier DOI
1305
Ship detection; Polarimetry; Compact polarimetry; Synthetic aperture
radar
BibRef
Liu, Z.Y.[Zhao-Ying],
Zhou, F.[Fugen],
Chen, X.W.[Xiao-Wu],
Bai, X.Z.[Xiang-Zhi],
Sun, C.M.[Chang-Ming],
Iterative infrared ship target segmentation based on multiple
features,
PR(47), No. 9, 2014, pp. 2839-2852.
Elsevier DOI
1406
Infrared ship target
BibRef
Liu, Z.Y.[Zhao-Ying],
Bai, X.Z.[Xiang-Zhi],
Sun, C.M.[Chang-Ming],
Zhou, F.[Fugen],
Li, Y.J.[Yu-Jian],
Infrared ship target segmentation through integration of multiple
feature maps,
IVC(48-49), No. 1, 2016, pp. 14-25.
Elsevier DOI
1604
Infrared images
BibRef
Bai, X.Z.[Xiang-Zhi],
Chen, Z.G.[Zhi-Guo],
Zhang, Y.[Yu],
Liu, Z.Y.[Zhao-Ying],
Lu, Y.[Yi],
Infrared Ship Target Segmentation Based on Spatial Information
Improved FCM,
Cyber(46), No. 12, December 2016, pp. 3259-3271.
IEEE DOI
1612
BibRef
Earlier:
Spatial information based FCM for infrared ship target segmentation,
ICIP14(5127-5131)
IEEE DOI
1502
Euclidean distance
Active contours
BibRef
Shi, Z.,
Yu, X.,
Jiang, Z.,
Li, B.,
Ship Detection in High-Resolution Optical Imagery Based on Anomaly
Detector and Local Shape Feature,
GeoRS(52), No. 8, August 2014, pp. 4511-4523.
IEEE DOI
1403
Detectors
BibRef
Teng, F.[Fei],
Liu, Q.[Qing],
Multi-scale ship tracking via random projections,
SIViP(8), No. 6, September 2014, pp. 1069-1076.
WWW Link.
1408
BibRef
Teng, F.[Fei],
Liu, Q.[Qing],
Robust multi-scale ship tracking via multiple compressed features
fusion,
SP:IC(31), No. 1, 2015, pp. 76-85.
Elsevier DOI
1502
Compressive sensing theory
BibRef
Tang, J.X.[Jie-Xiong],
Deng, C.W.[Chen-Wei],
Huang, G.B.[Guang-Bin],
Zhao, B.J.[Bao-Jun],
Compressed-Domain Ship Detection on Spaceborne Optical Image Using
Deep Neural Network and Extreme Learning Machine,
GeoRS(53), No. 3, March 2015, pp. 1174-1185.
IEEE DOI
1412
compressed sensing
BibRef
Gao, G.,
Wang, X.,
Lai, T.,
Detection of Moving Ships Based on a Combination of Magnitude and
Phase in Along-Track Interferometric SAR: Part I: SIMP Metric and Its
Performance,
GeoRS(53), No. 7, July 2015, pp. 3565-3581.
IEEE DOI
1503
Clutter
BibRef
Gao, G.,
Wang, X.,
Lai, T.,
Detection of Moving Ships Based on a Combination of Magnitude and
Phase in Along-Track Interferometric SAR: Part II: Statistical
Modeling and CFAR Detection,
GeoRS(53), No. 7, July 2015, pp. 3582-3599.
IEEE DOI
1503
Approximation methods
BibRef
Elvidge, C.D.[Christopher D.],
Zhizhin, M.[Mikhail],
Baugh, K.[Kimberly],
Hsu, F.C.[Feng-Chi],
Automatic Boat Identification System for VIIRS Low Light Imaging Data,
RS(7), No. 3, 2015, pp. 3020-3036.
DOI Link
1504
BibRef
Marino, A.[Armando],
Sanjuan-Ferrer, M.J.[Maria J.],
Hajnsek, I.[Irena],
Ouchi, K.[Kazuo],
Ship Detection with Spectral Analysis of Synthetic Aperture Radar:
A Comparison of New and Well-Known Algorithms,
RS(7), No. 5, 2015, pp. 5416-5439.
DOI Link
1506
BibRef
Wu, F.[Fan],
Wang, C.[Chao],
Jiang, S.F.[Shao-Feng],
Zhang, H.[Hong],
Zhang, B.[Bo],
Classification of Vessels in Single-Pol COSMO-SkyMed Images Based on
Statistical and Structural Features,
RS(7), No. 5, 2015, pp. 5511-5533.
DOI Link
1506
BibRef
Holtzhausen, P.J.,
Crnojevic, V.,
Herbst, B.M.,
An illumination invariant framework for real-time foreground detection,
RealTimeIP(10), No. 2, June 2015, pp. 423-433.
WWW Link.
1506
BibRef
Earlier:
The detection of naval vessels by fusion of edge and color background
models,
IPTA12(147-152)
IEEE DOI
1503
Gaussian processes
BibRef
Zhao, Y.[Ye],
Zhang, M.[Min],
Zhao, Y.W.[Yan-Wei],
Geng, X.P.[Xu-Pu],
A Bistatic SAR Image Intensity Model for the Composite Ship-Ocean
Scene,
GeoRS(53), No. 8, August 2015, pp. 4250-4258.
IEEE DOI
1506
geophysical image processing
BibRef
Huang, X.J.[Xiao-Jing],
Yang, W.[Wen],
Zhang, H.J.[Hai-Jian],
Xia, G.S.[Gui-Song],
Automatic Ship Detection in SAR Images Using Multi-Scale
Heterogeneities and an A Contrario Decision,
RS(7), No. 6, 2015, pp. 7695.
DOI Link
1507
BibRef
Touzi, R.,
Hurley, J.,
Vachon, P.W.,
Optimization of the Degree of Polarization for Enhanced Ship
Detection Using Polarimetric RADARSAT-2,
GeoRS(53), No. 10, October 2015, pp. 5403-5424.
IEEE DOI
1509
electromagnetic wave polarisation
BibRef
Wang, X.L.[Xiao-Long],
Chen, C.X.[Cui-Xia],
A fast line-scanning-based detection algorithm for real-time SAR ship
detection,
SIViP(9), No. 8, November 2015, pp. 1975-1982.
WWW Link.
1511
BibRef
Wang, X.L.[Xiao-Long],
Chen, C.X.[Cui-Xia],
Adaptive ship detection in SAR images using variance WIE-based method,
SIViP(10), No. 7, October 2016, pp. 1219-1224.
WWW Link.
1609
BibRef
Pelich, R.,
Longépé, N.,
Mercier, G.,
Hajduch, G.,
Garello, R.,
Vessel Refocusing and Velocity Estimation on SAR Imagery Using the
Fractional Fourier Transform,
GeoRS(54), No. 3, March 2016, pp. 1670-1684.
IEEE DOI
1603
Acceleration
BibRef
Gómez-Enri, J.[Jesús],
Scozzari, A.[Andrea],
Soldovieri, F.[Francesco],
Coca, J.[Josep],
Vignudelli, S.[Stefano],
Detection and Characterization of Ship Targets Using CryoSat-2
Altimeter Waveforms,
RS(8), No. 3, 2016, pp. 193.
DOI Link
1604
BibRef
Gómez-Enri, J.[Jesús],
Cipollini, P.,
Passaro, M.,
Vignudelli, S.[Stefano],
Tejedor, B.,
Coca, J.[Josep],
Coastal Altimetry Products in the Strait of Gibraltar,
GeoRS(54), No. 9, September 2016, pp. 5455-5466.
IEEE DOI
1609
height measurement
BibRef
Gao, G.,
Luo, Y.,
Ouyang, K.,
Zhou, S.,
Statistical Modeling of PMA Detector for Ship Detection in
High-Resolution Dual-Polarization SAR Images,
GeoRS(54), No. 7, July 2016, pp. 4302-4313.
IEEE DOI
1606
Adaptation models
BibRef
Gao, G.,
Ouyang, K.,
Luo, Y.,
Liang, S.,
Zhou, S.,
Scheme of Parameter Estimation for Generalized Gamma Distribution and
Its Application to Ship Detection in SAR Images,
GeoRS(55), No. 3, March 2017, pp. 1812-1832.
IEEE DOI
1703
Clutter
BibRef
Graziano, M.D.[Maria Daniela],
D'Errico, M.[Marco],
Rufino, G.[Giancarlo],
Wake Component Detection in X-Band SAR Images for Ship Heading and
Velocity Estimation,
RS(8), No. 6, 2016, pp. 498.
DOI Link
1608
BibRef
Xu, L.[Lu],
Zhang, H.[Hong],
Wang, C.[Chao],
Zhang, B.[Bo],
Tian, S.[Sirui],
Compact Polarimetric SAR Ship Detection with m-d Decomposition Using
Visual Attention Model,
RS(8), No. 9, 2016, pp. 751.
DOI Link
1610
BibRef
Zou, Z.,
Shi, Z.,
Ship Detection in Spaceborne Optical Image With SVD Networks,
GeoRS(54), No. 10, October 2016, pp. 5832-5845.
IEEE DOI
1610
neural nets
BibRef
Heiselberg, H.[Henning],
A Direct and Fast Methodology for Ship Recognition in Sentinel-2
Multispectral Imagery,
RS(8), No. 12, 2016, pp. 1033.
DOI Link
1612
BibRef
Dijk, J.[Judith],
Schutte, K.[Klamer],
Nieuwenhuizen, R.[Robert],
Gagnon, M.A.[Marc-André],
Gagnon, J.P.[Jean-Philippe],
Tremblay, P.[Pierre],
Savary, S.[Simon],
Farley, V.[Vincent],
Lagueux, P.[Philippe],
Chamberland, M.[Martin],
Infrared hyperspectral imaging of ship plumes,
SPIE(Newsroom), November 22, 2016.
DOI Link
1612
Characterizing the spectral features of exhaust gases via IR
hyperspectral detection enables the standoff detection of distant
ships.
BibRef
Gan, S.,
Liang, S.,
Li, K.,
Deng, J.,
Cheng, T.,
Long-Term Ship Speed Prediction for Intelligent Traffic Signaling,
ITS(18), No. 1, January 2017, pp. 82-91.
IEEE DOI
1701
Communication system signaling
BibRef
Wang, S.,
Wang, M.,
Yang, S.,
Jiao, L.,
New Hierarchical Saliency Filtering for Fast Ship Detection in
High-Resolution SAR Images,
GeoRS(55), No. 1, January 2017, pp. 351-362.
IEEE DOI
1701
geophysical techniques
BibRef
Patroumpas, K.[Kostas],
Alevizos, E.[Elias],
Artikis, A.[Alexander],
Vodas, M.[Marios],
Pelekis, N.[Nikos],
Theodoridis, Y.[Yannis],
Online event recognition from moving vessel trajectories,
GeoInfo(21), No. 2, April 2017, pp. 389-427.
Springer DOI
1702
BibRef
Zhu, J.W.[Ji-Wei],
Qiu, X.L.[Xiao-Lan],
Pan, Z.X.[Zong-Xu],
Zhang, Y.T.[Yue-Ting],
Lei, B.[Bin],
An Improved Shape Contexts Based Ship Classification in SAR Images,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link
1703
BibRef
Greidanus, H.[Harm],
Alvarez, M.[Marlene],
Santamaria, C.[Carlos],
Thoorens, F.X.[François-Xavier],
Kourti, N.[Naouma],
Argentieri, P.[Pietro],
The SUMO Ship Detector Algorithm for Satellite Radar Images,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Bloisi, D.D.,
Previtali, F.,
Pennisi, A.,
Nardi, D.,
Fiorini, M.,
Enhancing Automatic Maritime Surveillance Systems With Visual
Information,
ITS(18), No. 4, April 2017, pp. 824-833.
IEEE DOI
1704
Artificial intelligence
BibRef
Xu, F.[Fang],
Liu, J.H.[Jing-Hong],
Sun, M.C.[Ming-Chao],
Zeng, D.D.[Dong-Dong],
Wang, X.[Xuan],
A Hierarchical Maritime Target Detection Method for Optical Remote
Sensing Imagery,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Dong, L.,
Wang, B.,
Zhao, M.,
Xu, W.,
Robust Infrared Maritime Target Detection Based on Visual Attention
and Spatiotemporal Filtering,
GeoRS(55), No. 5, May 2017, pp. 3037-3050.
IEEE DOI
1705
fog, geophysical image processing, image filtering,
object detection, ocean waves, remote sensing,
antivibration pipeline-filtering algorithm,
image background smoothness, image border, infrared imager,
infrared maritime target detection method,
multiframe-based clutter removal method, ocean wave,
pipeline-filtering model, saliency map,
saliency singularity evaluation, sea fog, sea glint,
single-frame target detection strategy,
target detection algorithm, visual attention model, Clutter,
Computational modeling, Image color analysis, Object detection,
Ocean waves, Robustness, Visualization, Image segmentation,
infrared imaging, infrared surveillance, object, detection
BibRef
He, H.,
Lin, Y.,
Chen, F.,
Tai, H.M.,
Yin, Z.,
Inshore Ship Detection in Remote Sensing Images via Weighted Pose
Voting,
GeoRS(55), No. 6, June 2017, pp. 3091-3107.
IEEE DOI
1706
Marine vehicles, Remote sensing, Robustness, Satellites, Shape,
Surveillance, Inshore ship detection, pose weighted voting,
radial gradient angle (RGA), satellite image, shape-similar, distractor
BibRef
Lin, H.N.[Hao-Ning],
Shi, Z.W.[Zhen-Wei],
Zou, Z.X.[Zheng-Xia],
Maritime Semantic Labeling of Optical Remote Sensing Images with
Multi-Scale Fully Convolutional Network,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link
1706
sea-land segmentation and ship detection.
BibRef
Xi, Y.Y.[Yu-Yang],
Lang, H.T.[Hai-Tao],
Tao, Y.H.[Yun-Hong],
Huang, L.[Lin],
Pei, Z.[Zijun],
Four-Component Model-Based Decomposition for Ship Targets Using
PolSAR Data,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Nie, T.[Ting],
He, B.[Bin],
Bi, G.[Guoling],
Zhang, Y.[Yu],
Wang, W.[Wensheng],
A Method of Ship Detection under Complex Background,
IJGI(6), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Prasad, D.K.,
Rajan, D.,
Rachmawati, L.,
Rajabally, E.,
Quek, C.,
Video Processing From Electro-Optical Sensors for Object Detection
and Tracking in a Maritime Environment: A Survey,
ITS(18), No. 8, August 2017, pp. 1993-2016.
IEEE DOI
1708
Cameras, Image edge detection, Intelligent sensors,
Marine vehicles, Object detection, Radar tracking,
Maritime vehicles, autonomous automobiles, computer vision,
maritime navigation, video, signal, processing
BibRef
Santamaria, C.[Carlos],
Alvarez, M.[Marlene],
Greidanus, H.[Harm],
Syrris, V.[Vasileios],
Soille, P.[Pierre],
Argentieri, P.[Pietro],
Mass Processing of Sentinel-1 Images for Maritime Surveillance,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Kang, M.[Miao],
Ji, K.F.[Ke-Feng],
Leng, X.G.[Xiang-Guang],
Lin, Z.[Zhao],
Contextual Region-Based Convolutional Neural Network with Multilayer
Fusion for SAR Ship Detection,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Chen, Z.C.[Ze-Chuang],
Li, B.[Bin],
Tian, L.F.[Lian Fang],
Chao, D.[Dong],
Automatic detection and tracking of ship based on mean shift in
corrected video sequences,
ICIVC17(449-453)
IEEE DOI
1708
Complexity theory, Image segmentation, Imaging, Marine vehicles,
Mathematical model, Target tracking, Transforms, image correction,
image segmentation, mean shift algorithm, ship, tracking
BibRef
Gundogdu, E.[Erhan],
Solmaz, B.[Berkan],
Yücesoy, V.[Veysel],
Koç, A.[Aykut],
MARVEL: A Large-Scale Image Dataset for Maritime Vessels,
ACCV16(V: 165-180).
Springer DOI
1704
Dataset, Ships.
BibRef
Cane, T.,
Ferryman, J.M.,
Saliency-Based Detection for Maritime Object Tracking,
PETS16(1257-1264)
IEEE DOI
1612
BibRef
Cruz, G.[Gonçalo],
Bernardino, A.[Alexandre],
Aerial Detection in Maritime Scenarios Using Convolutional Neural
Networks,
ACIVS16(373-384).
Springer DOI
1611
BibRef
Bousetouane, F.,
Morris, B.,
Fast CNN surveillance pipeline for fine-grained vessel classification
and detection in maritime scenarios,
AVSS16(242-248)
IEEE DOI
1611
Detectors
BibRef
Haigang, S.[Sui],
Zhina, S.[Song],
A Novel Ship Detection Method For Large-scale Optical Satellite Images
Based On Visual Lbp Feature And Visual Attention Model,
ISPRS16(B3: 917-921).
DOI Link
1610
BibRef
Zhang, R.Q.[Rui-Qian],
Yao, J.[Jian],
Zhang, K.[Kao],
Feng, C.[Chen],
Zhang, J.D.[Jia-Dong],
S-CNN-Based Ship Detection from High-Resolution Remote Sensing Images,
ISPRS16(B7: 423-430).
DOI Link
1610
BibRef
Negula, I.D.[I. Dana],
Poenaru, V.D.,
Olteanu, V.G.,
Badea, A.,
Sentinel-1/2 Data For Ship Traffic Monitoring On The Danube River,
ISPRS16(B8: 37-41).
DOI Link
1610
BibRef
Schaum, A.,
Allman, E.,
Leathers, R.A.,
Spectral ship surveillance from space,
AIPR15(1-8)
IEEE DOI
1605
aerospace instrumentation
BibRef
Bousetouane, F.[Fouad],
Morris, B.[Brendan],
Off-the-Shelf CNN Features for Fine-Grained Classification of Vessels
in a Maritime Environment,
ISVC15(II: 379-388).
Springer DOI
1601
BibRef
Arguedas, V.F.[Virginia Fernandez],
Texture-based vessel classifier for electro-optical satellite imagery,
ICIP15(3866-3870)
IEEE DOI
1512
SAR
BibRef
Martin-de-Nicolas, J.,
Jarabo-Amores, P.,
Rey-Maestre, N.,
Mata-Moya, D.,
Barcena-Humanes, J.L.,
A non-parametric CFAR detector based on SAR sea clutter statistical
modeling,
ICIP15(4426-4430)
IEEE DOI
1512
CFAR; Synthetic aperture radar; clutter modeling; ship detection
BibRef
Osborne, C.,
Cane, T.,
Nawaz, T.,
Ferryman, J.M.,
Temporally stable feature clusters for maritime object tracking in
visible and thermal imagery,
AVSS15(1-6)
IEEE DOI
1511
infrared imaging
BibRef
Zhang, M.M.[Mabel M.],
Choi, J.[Jean],
Daniilidis, K.[Kostas],
Wolf, M.T.[Michael T.],
Kanan, C.[Christopher],
VAIS: A dataset for recognizing maritime imagery in the visible and
infrared spectrums,
PBVS15(10-16)
IEEE DOI
1510
Cameras
BibRef
Grimaldi, M.,
Bechar, I.,
Lelore, T.,
Guis, V.,
Bouchara, F.,
An unsupervised approach to automatic object extraction from a
maritime video scene,
IPTA14(1-6)
IEEE DOI
1503
geometry
BibRef
Wang, T.[Tao],
Bai, X.Z.[Xiang-Zhi],
Zhang, Y.[Yu],
Multiple Features Based Low-Contrast Infrared Ship Image Segmentation
Using Fuzzy Inference System,
DICTA14(1-6)
IEEE DOI
1502
feature extraction
BibRef
Liu, Z.Y.[Zhao-Ying],
Sun, C.M.[Chang-Ming],
Bai, X.Z.[Xiang-Zhi],
Zhou, F.[Fugen],
Infrared Ship Target Image Smoothing Based on Adaptive Mean Shift,
DICTA14(1-8)
IEEE DOI
1502
image denoising
BibRef
Sun, Y.[Yuan],
Zhang, B.[Bo],
Wang, C.[Chao],
Wu, F.[Fan],
Ship detection based on eigenvalue-eigenvector decomposition and
OS-CFAR detector,
CVRS12(350-355).
IEEE DOI
1302
BibRef
Chen, W.T.[Wen-Ting],
Ji, K.F.[Ke-Feng],
Xing, X.W.[Xiang-Wei],
Zou, H.X.[Huan-Xin],
Sun, H.[Hao],
Ship recognition in high resolution SAR imagery based on feature
selection,
CVRS12(301-305).
IEEE DOI
1302
BibRef
Lu, C.Y.[Chun-Yan],
Zou, H.X.[Huan-Xin],
Zhou, S.L.[Shi-Lin],
Sun, H.[Hao],
An association algorithm of ship-group targets based on topological and
attributive characteristics,
CVRS12(34-38).
IEEE DOI
1302
BibRef
Jiang, S.F.[Shao-Feng],
Wu, F.[Fan],
Wang, C.[Chao],
Zhang, B.[Bo],
Civilian vessel classification with COSMO-SkyMed images based on
feature analysis,
CVRS12(279-284).
IEEE DOI
1302
BibRef
Huang, G.P.[Gao-Pan],
Wang, Y.Q.[Yan-Qing],
Zhang, Y.S.[Yu-Shuang],
Tian, Y.[Yuan],
Ship Detection Using Texture Statistics from Optical Satellite Images,
DICTA11(507-512).
IEEE DOI
1205
BibRef
Rainey, K.[Katie],
Stastny, J.[John],
Object recognition in ocean imagery using feature selection and
compressive sensing,
AIPR11(1-6).
IEEE DOI
1204
BibRef
Harguess, J.[Josh],
Rainey, K.[Katie],
Are face recognition methods useful for classifying ships?,
AIPR11(1-7).
IEEE DOI
1204
BibRef
Yang, G.[Guang],
Lu, Q.[Qichao],
Gao, F.[Feng],
A Novel Ship Detection Method Based on Sea State Analysis from Optical
Imagery,
ICIG11(466-471).
IEEE DOI
1109
BibRef
You, X.[Xin],
Yu, N.H.[Neng-Hai],
An Automatic Matching Algorithm Based on SIFT Descriptors for Remote
Sensing Ship Image,
ICIG11(377-381).
IEEE DOI
1109
BibRef
Xia, Y.[Yu],
Wan, S.H.[Shou-Hong],
Yue, L.[Lihua],
A Novel Algorithm for Ship Detection Based on Dynamic Fusion Model of
Multi-feature and Support Vector Machine,
ICIG11(521-526).
IEEE DOI
1109
BibRef
Xie, H.[Hong],
Li, L.L.[Lin-Lin],
Bo, H.[Hua],
Zhang, Y.N.[Yun-Nong],
A Novel Method for Ship Detection Based on NSCT and ACO,
CISP09(1-4).
IEEE DOI
0910
BibRef
Zhuo, C.[Chen],
An Improved Automatic Ship Detection Method in SAR Images,
CISP09(1-4).
IEEE DOI
0910
BibRef
Li, W.B.[Wei-Bin],
He, M.Y.[Ming-Yi],
Zhang, S.L.[Shun-Li],
A Heterogeneity-Based Ship Detection Algorithm for SAR Imagery,
CISP09(1-5).
IEEE DOI
0910
BibRef
Gagnon, L.,
Klepko, R.,
Hierarchical Classifier Design for Airborne SAR Images of Ships,
SPIE(3371), 1998, pp. xx
PDF File.
BibRef
9800
Osman, H.[Hossam],
Pan, L.,
Blostein, S.D.[Steven D.],
Gagnon, L.,
Classification of Ships in Airborne SAR Imagery
Using Backpropagation Neural Networks,
SPIE(3161), July 1997 pp. 126-136.
BibRef
9707
Gouaillier, V.,
Gagnon, L.,
Ship Silhouette Recognition Using Principal Components Analysis,
SPIE(3164), July 1997, pp. 59-69.
PDF File.
BibRef
9707
Chapter on Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR continues in
ATR -- IR, Infra-Red, Thermal, Applications .