22.9.4.1 ATR -- Vehicles, Aerial Images, Ship Detection

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.
DOI 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

Gan, S., Liang, S., Li, K., Deng, J., Cheng, T.,
Trajectory Length Prediction for Intelligent Traffic Signaling: A Data-Driven Approach,
ITS(19), No. 2, February 2018, pp. 426-435.
IEEE DOI 1802
Intelligent transportation systems, Marine vehicles, Prediction algorithms, Predictive models, Rivers, intelligent traffic signalling system (ITSS) 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

Xu, F.[Fang], Liu, J.H.[Jing-Hong], Dong, C.[Chao], Wang, X.[Xuan],
Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Dong, C.[Chao], Liu, J.H.[Jing-Hong], Xu, F.[Fang],
Ship Detection in Optical Remote Sensing Images Based on Saliency and a Rotation-Invariant Descriptor,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
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, 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

Graziano, M.D.[Maria Daniela], Grasso, M.[Marco], d'Errico, M.[Marco],
Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Yao, S.[Shun], Chang, X.L.[Xue-Li], Cheng, Y.F.[Yu-Feng], Jin, S.Y.[Shu-Ying], Zuo, D.S.[De-Shan],
Detection of Moving Ships in Sequences of Remote Sensing Images,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Ma, F.[Feng], Chen, Y.W.[Yu-Wang], Yan, X.P.[Xin-Ping], Chu, X.M.[Xiu-Min], Wang, J.[Jin],
Target recognition for coastal surveillance based on radar images and generalised Bayesian inference,
IET-ITS(12), No. 2, March 2018, pp. 103-112.
DOI Link 1801
BibRef

Yang, X.[Xue], Sun, H.[Hao], Fu, K.[Kun], Yang, J.[Jirui], Sun, X.[Xian], Yan, M.L.[Meng-Long], Guo, Z.[Zhi],
Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Lin, H.P.[Hui-Ping], Song, S.[Shengli], Yang, J.[Jian],
Ship Classification Based on MSHOG Feature and Task-Driven Dictionary Learning with Structured Incoherent Constraints in SAR Images,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Gierull, C.H., Sikaneta, I.,
A Compound-Plus-Noise Model for Improved Vessel Detection in Non-Gaussian SAR Imagery,
GeoRS(56), No. 3, March 2018, pp. 1444-1453.
IEEE DOI 1804
computational complexity, probability, radar clutter, radar detection, radar imaging, synthetic aperture radar, synthetic aperture radar (SAR) BibRef

Gallego, A.J.[Antonio-Javier], Pertusa, A.[Antonio], Gil, P.[Pablo],
Automatic Ship Classification from Optical Aerial Images with Convolutional Neural Networks,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Rikka, S.[Sander], Pleskachevsky, A.[Andrey], Jacobsen, S.[Sven], Alari, V.[Victor], Uiboupin, R.[Rivo],
Meteo-Marine Parameters from Sentinel-1 SAR Imagery: Towards Near Real-Time Services for the Baltic Sea,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Zhang, T.[Tao], Marino, A.[Armando], Xiong, H.L.[Hui-Lin], Yu, W.X.[Wen-Xian],
A Ship Detector Applying Principal Component Analysis to the Polarimetric Notch Filter,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Sun, Y.X., Liu, P., Jin, Y.Q.,
Ship Wake Components: Isolation, Reconstruction, and Characteristics Analysis in Spectral, Spatial, and TerraSAR-X Image Domains,
GeoRS(56), No. 7, July 2018, pp. 4209-4224.
IEEE DOI 1807
Dispersion, Image reconstruction, Kelvin, Marine vehicles, Shape, Spectral analysis, Synthetic aperture radar, synthetic aperture radar (SAR) image BibRef

Wang, Y., Chen, X.,
3-D Interferometric Inverse Synthetic Aperture Radar Imaging of Ship Target With Complex Motion,
GeoRS(56), No. 7, July 2018, pp. 3693-3708.
IEEE DOI 1807
Doppler radar, Imaging, Marine vehicles, Radar imaging, Radar scattering, Solid modeling, ship target BibRef

Similä, M.[Markku], Lensu, M.[Mikko],
Estimating the Speed of Ice-Going Ships by Integrating SAR Imagery and Ship Data from an Automatic Identification System,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Ma, H., Antoniou, M., Stove, A.G., Winkel, J., Cherniakov, M.,
Maritime Moving Target Localization Using Passive GNSS-Based Multistatic Radar,
GeoRS(56), No. 8, August 2018, pp. 4808-4819.
IEEE DOI 1808
passive radar, satellite navigation, target tracking, maritime moving target localization, target localization BibRef

Li, B., Liu, B., Guo, W., Zhang, Z., Yu, W.,
Ship Size Extraction for Sentinel-1 Images Based on Dual-Polarization Fusion and Nonlinear Regression: Push Error Under One Pixel,
GeoRS(56), No. 8, August 2018, pp. 4887-4905.
IEEE DOI 1808
gradient methods, image fusion, marine radar, radar imaging, regression analysis, ships, synthetic aperture radar, synthetic aperture radar (SAR) image BibRef

Shao, Z., Wu, W., Wang, Z., Du, W., Li, C.,
SeaShips: A Large-Scale Precisely Annotated Dataset for Ship Detection,
MultMed(20), No. 10, October 2018, pp. 2593-2604.
IEEE DOI 1810
image segmentation, object detection, ships, video signal processing, video surveillance, ship types, SeaShips, ship detection BibRef

Aziz, K.[Kheireddine], Bouchara, F.[Frédéric],
Multimodal Deep Learning for Robust Recognizing Maritime Imagery in the Visible and Infrared Spectrums,
ICIAR18(235-244).
Springer DOI 1807
BibRef

Brauchle, J.[Jörg], Bayer, S.[Steven], Berger, R.[Ralf],
Automatic Ship Detection on Multispectral and Thermal Infrared Aerial Images Using MACS-Mar Remote Sensing Platform,
PSIVTWS17(382-395).
Springer DOI 1806
BibRef

Liu, Z., Hu, J., Weng, L., Yang, Y.,
Rotated region based CNN for ship detection,
ICIP17(900-904)
IEEE DOI 1803
Convolution, Feature extraction, Marine vehicles, Object detection, Proposals, Task analysis, Training, Rotated region, ship detection BibRef

van Persie, M., Noorbergen, H.H.S., Oostdijk, A.,
Harbour pattern of life analysis with time series of medium resolution satellite images,
MultiTemp17(1-3)
IEEE DOI 1712
remote sensing, Erdas imagine environment, Harbour Pattern, Landsat imagery, Sentinel imagery, UrtheCast, ship detection BibRef

Li, Z.[Zhi], Qu, C.W.[Chang-Wen], Zhou, Q.[Qiang], Liu, C.[Chen], Peng, S.J.[Shu-Juan], Li, J.W.[Jian-Wei],
Ship detection in harbor area in SAR images based on constructing an accurate sea-clutter model,
ICIVC17(13-19)
IEEE DOI 1708
Clutter, Fitting, Image segmentation, Marine vehicles, Mathematical model, Strips, constant false alarm rate, ship detection, the SAR image, and-sea segmentation, port area, sea clutter model 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],
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Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
ATR -- IR, Infra-Red, Thermal, Applications .