Boat Detection,
Online2019
HTML Version.
Dataset, Ships.
1911
WWW Link.
Public video dataset for boat detection/tracking from UAV video footage
See also MULTIDRONE.
See also Racing Bicycle Detection/Tracking from UAV Footage, UAV Detection.
BibRef
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
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, 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
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
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
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
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
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
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
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
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
Yang, X.[Xue],
Sun, H.[Hao],
Fu, K.[Kun],
Yang, J.R.[Ji-Rui],
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
Fu, K.[Kun],
Chang, Z.H.[Zhong-Han],
Zhang, Y.[Yue],
Xu, G.L.[Guang-Luan],
Zhang, K.[Keshu],
Sun, X.[Xian],
Rotation-Aware and Multi-Scale Convolutional Neural Network for
Object Detection in Remote Sensing Images,
PandRS(161), 2020, pp. 294-308.
Elsevier DOI
2002
Convolutional neural networks, Objection detection,
Remote sensing images, Rotation aware, Multi-scale
BibRef
Fu, K.[Kun],
Chen, Z.[Zhuo],
Zhang, Y.[Yue],
Sun, X.[Xian],
Enhanced Feature Representation in Detection for Optical Remote
Sensing Images,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link
1909
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
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
Li, Q.,
Mou, L.,
Liu, Q.,
Wang, Y.,
Zhu, X.X.,
HSF-Net: Multiscale Deep Feature Embedding for Ship Detection in
Optical Remote Sensing Imagery,
GeoRS(56), No. 12, December 2018, pp. 7147-7161.
IEEE DOI
1812
Marine vehicles, Feature extraction, Remote sensing,
Object detection, Proposals, Optical sensors, Optical imaging,
remote sensing
BibRef
Zhu, C.Y.[Chen-Yang],
Garcia, H.[Heriberto],
Kaplan, A.[Anna],
Schinault, M.[Matthew],
Handegard, N.O.[Nils Olav],
Godř, O.R.[Olav Rune],
Huang, W.[Wei],
Ratilal, P.[Purnima],
Detection, Localization and Classification of Multiple Mechanized
Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean
Acoustic Waveguide Remote Sensing,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Zhao, M.,
Yao, X.,
Sun, J.,
Zhang, S.,
Bai, J.,
GIS-Based Simulation Methodology for Evaluating Ship Encounters
Probability to Improve Maritime Traffic Safety,
ITS(20), No. 1, January 2019, pp. 323-337.
IEEE DOI
1901
Marine vehicles, Transportation, Analytical models, Accidents,
Object oriented modeling, Geographic information systems, Safety,
maritime traffic safety
BibRef
Alessandrini, A.,
Mazzarella, F.,
Vespe, M.,
Estimated Time of Arrival Using Historical Vessel Tracking Data,
ITS(20), No. 1, January 2019, pp. 7-15.
IEEE DOI
1901
Artificial intelligence, Marine vehicles, Estimation, Safety,
Security, Data mining, Radar tracking, Estimated time of arrival,
port operations
BibRef
Fu, K.[Kun],
Li, Y.[Yang],
Sun, H.[Hao],
Yang, X.[Xue],
Xu, G.L.[Guang-Luan],
Li, Y.T.[Yu-Ting],
Sun, X.[Xian],
A Ship Rotation Detection Model in Remote Sensing Images Based on
Feature Fusion Pyramid Network and Deep Reinforcement Learning,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Wang, N.[Nan],
Li, B.[Bo],
Xu, Q.Z.[Qi-Zhi],
Wang, Y.H.[Yong-Hua],
Automatic Ship Detection in Optical Remote Sensing Images Based on
Anomaly Detection and SPP-PCANet,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Xu, X.D.[Xiao-Dong],
Li, W.[Wei],
Ran, Q.[Qiong],
Du, Q.[Qian],
Gao, L.R.[Lian-Ru],
Zhang, B.[Bing],
Multisource Remote Sensing Data Classification Based on Convolutional
Neural Network,
GeoRS(56), No. 2, February 2018, pp. 937-949.
IEEE DOI
1802
Convolution, Data mining, Feature extraction, Laser radar,
Neural networks, Remote sensing, Support vector machines,
hyperspectral imagery (HSI)
BibRef
Shi, Q.Q.[Qiao-Qiao],
Li, W.[Wei],
Tao, R.[Ran],
Sun, X.[Xu],
Gao, L.R.[Lian-Ru],
Ship Classification Based on Multifeature Ensemble with Convolutional
Neural Network,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Wang, Y.Y.[Yuan-Yuan],
Wang, C.[Chao],
Zhang, H.[Hong],
Dong, Y.[Yingbo],
Wei, S.[Sisi],
Automatic Ship Detection Based on RetinaNet Using Multi-Resolution
Gaofen-3 Imagery,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Zhang, S.M.[Shao-Ming],
Wu, R.[Ruize],
Xu, K.[Kunyuan],
Wang, J.M.[Jian-Mei],
Sun, W.W.[Wei-Wei],
R-CNN-Based Ship Detection from High Resolution Remote Sensing
Imagery,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Wen, Y.Q.[Yuan-Qiao],
Zhang, Y.M.[Yi-Meng],
Huang, L.[Liang],
Zhou, C.H.[Chun-Hui],
Xiao, C.S.[Chang-Shi],
Zhang, F.[Fan],
Peng, X.[Xin],
Zhan, W.Q.[Wen-Qiang],
Sui, Z.Y.[Zhong-Yi],
Semantic Modelling of Ship Behavior in Harbor Based on Ontology and
Dynamic Bayesian Network,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Yao, Y.[Yuan],
Jiang, Z.G.[Zhi-Guo],
Zhang, H.[Haopeng],
Zhou, Y.[Yu],
On-Board Ship Detection in Micro-Nano Satellite Based on Deep
Learning and COTS Component,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Caillec, J.M.L.[Jean-Marc Le],
Habonneau, J.[Jérôme],
Khenchaf, A.[Ali],
Ship Profile Imaging Using Multipath Backscattering,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Prasad, D.K.,
Prasath, C.K.,
Rajan, D.,
Rachmawati, L.,
Rajabally, E.,
Quek, C.,
Object Detection in a Maritime Environment:
Performance Evaluation of Background Subtraction Methods,
ITS(20), No. 5, May 2019, pp. 1787-1802.
IEEE DOI
1905
Adaptation models, Videos, Gaussian distribution, Object detection,
Benchmark testing, Cameras, Vehicle dynamics, Maritime vehicles,
computer vision
BibRef
Wang, L.,
Zhang, M.,
Chen, J.,
Investigation on the Electromagnetic Scattering From the Accurate 3-D
Breaking Ship Waves Generated by CFD Simulation,
GeoRS(57), No. 5, May 2019, pp. 2689-2699.
IEEE DOI
1905
computational fluid dynamics, electromagnetic wave scattering,
flow simulation, geometry, iterative methods, physical optics, ships,
composite scattering
BibRef
Hsu, F.C.[Feng-Chi],
Elvidge, C.D.[Christopher D.],
Baugh, K.[Kimberly],
Zhizhin, M.[Mikhail],
Ghosh, T.[Tilottama],
Kroodsma, D.[David],
Susanto, A.[Adi],
Budy, W.[Wiryawan],
Riyanto, M.[Mochammad],
Nurzeha, R.[Ridwan],
Sudarja, Y.[Yeppi],
Cross-Matching VIIRS Boat Detections with Vessel Monitoring System
Tracks in Indonesia,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Wang, W.X.[Wen-Xiu],
Fu, Y.T.[Yu-Tian],
Dong, F.[Feng],
Li, F.[Feng],
Semantic segmentation of remote sensing ship image via a convolutional
neural networks model,
IET-IPR(13), No. 6, 10 May 2019, pp. 1016-1022.
DOI Link
1906
BibRef
Zhou, H.,
Jiang, T.,
Decision Tree Based Sea-Surface Weak Target Detection With False
Alarm Rate Controllable,
SPLetters(26), No. 6, June 2019, pp. 793-797.
IEEE DOI
1906
decision trees, feature extraction, fractals,
learning (artificial intelligence), object detection,
decision tree
BibRef
Liu, Z.Q.[Zhi-Quan],
Practical backstepping control for underactuated ship path following
associated with disturbances,
IET-ITS(13), No. 5, May 2019, pp. 834-840.
DOI Link
1906
BibRef
Wen, G.,
Ge, S.S.,
Chen, C.L.P.,
Tu, F.,
Wang, S.,
Adaptive Tracking Control of Surface Vessel Using Optimized
Backstepping Technique,
Cyber(49), No. 9, Sep. 2019, pp. 3420-3431.
IEEE DOI
1907
adaptive control, control nonlinearities,
control system synthesis, feedback,
surface vessel
BibRef
Dong, C.[Chao],
Liu, J.[Jinghong],
Xu, F.[Fang],
Liu, C.L.[Cheng-Long],
Ship Detection from Optical Remote Sensing Images Using Multi-Scale
Analysis and Fourier HOG Descriptor,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link
1907
BibRef
Wang, B.,
Motai, Y.,
Dong, L.,
Xu, W.,
Detecting Infrared Maritime Targets Overwhelmed in Sun Glitters by
Antijitter Spatiotemporal Saliency,
GeoRS(57), No. 7, July 2019, pp. 5159-5173.
IEEE DOI
1907
Sun, Spatiotemporal phenomena, Visualization, Jitter,
Object detection, Imaging, Generators, Image segmentation,
target detection
BibRef
Yan, Y.M.[Yi-Ming],
Tan, Z.[Zhichao],
Su, N.[Nan],
A Data Augmentation Strategy Based on Simulated Samples for Ship
Detection in RGB Remote Sensing Images,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Feng, Y.[Yingchao],
Diao, W.H.[Wen-Hui],
Sun, X.[Xian],
Yan, M.L.[Meng-Long],
Gao, X.[Xin],
Towards Automated Ship Detection and Category Recognition from
High-Resolution Aerial Images,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Cruz, G.,
Bernardino, A.,
Learning Temporal Features for Detection on Maritime Airborne Video
Sequences Using Convolutional LSTM,
GeoRS(57), No. 9, September 2019, pp. 6565-6576.
IEEE DOI
1909
Feature extraction, Aircraft, Boats, Visualization, Video sequences,
Detectors, Monitoring, Object detection, recurrent neural networks,
remote monitoring
BibRef
Zhou, X.Y.[Xing-Yue],
Yang, K.[Kunde],
Duan, R.[Rui],
Deep Learning Based on Striation Images for Underwater and Surface
Target Classification,
SPLetters(26), No. 9, September 2019, pp. 1378-1382.
IEEE DOI
1909
belief networks, convolutional neural nets, image classification,
interference (signal), learning (artificial intelligence),
sonar images
BibRef
You, Y.[Yanan],
Li, Z.[Zezhong],
Ran, B.[Bohao],
Cao, J.Y.[Jing-Yi],
Lv, S.[Sudi],
Liu, F.[Fang],
Broad Area Target Search System for Ship Detection via Deep
Convolutional Neural Network,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Ma, J.L.[Jin-Lei],
Zhou, Z.Q.[Zhi-Qiang],
Wang, B.[Bo],
Zong, H.[Hua],
Wu, F.[Fei],
Ship Detection in Optical Satellite Images via Directional Bounding
Boxes Based on Ship Center and Orientation Prediction,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Ribeiro, R.,
Cruz, G.,
Matos, J.,
Bernardino, A.,
A Data Set for Airborne Maritime Surveillance Environments,
CirSysVideo(29), No. 9, September 2019, pp. 2720-2732.
IEEE DOI
1909
Cameras, Surveillance, Aircraft, Boats, Hyperspectral imaging,
Labeling, Image databases, hyperspectral imaging, video surveillance
BibRef
Xiao, X.[Xiaowu],
Zhou, Z.Q.[Zhi-Qiang],
Wang, B.[Bo],
Li, L.H.[Lin-Hao],
Miao, L.J.[Ling-Juan],
Ship Detection under Complex Backgrounds Based on Accurate Rotated
Anchor Boxes from Paired Semantic Segmentation,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Chen, H.,
Gao, T.,
Chen, W.,
Zhang, Y.,
Zhao, J.,
Contour Refinement and EG-GHT-Based Inshore Ship Detection in Optical
Remote Sensing Image,
GeoRS(57), No. 11, November 2019, pp. 8458-8478.
IEEE DOI
1911
Marine vehicles, Feature extraction, Head, Shape, Indexes, Training,
Strain, Border scoring, curvature filtering,
structured binarization feature (SBF)
BibRef
Du, J.,
Hu, X.,
Sun, Y.,
Adaptive Robust Nonlinear Control Design for Course Tracking of Ships
Subject to External Disturbances and Input Saturation,
SMCS(50), No. 1, January 2020, pp. 193-202.
IEEE DOI
2001
Marine vehicles, Adaptive systems, Control design,
Nonlinear dynamical systems, Adaptation models, Navigation,
ship steering system
BibRef
Tian, T.[Tian],
Pan, Z.H.[Zhi-Hong],
Tan, X.Y.[Xiang-Yu],
Chu, Z.Q.[Zheng-Quan],
Arbitrary-Oriented Inshore Ship Detection based on Multi-Scale
Feature Fusion and Contextual Pooling on Rotation Region Proposals,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Wu, Y.[Yue],
Ma, W.P.[Wen-Ping],
Gong, M.[Maoguo],
Bai, Z.F.[Zhuang-Fei],
Zhao, W.[Wei],
Guo, Q.Q.[Qiong-Qiong],
Chen, X.B.[Xiao-Bo],
Miao, Q.G.[Qi-Guang],
A Coarse-to-Fine Network for Ship Detection in Optical Remote Sensing
Images,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Nie, T.[Ting],
Han, X.[Xiyu],
He, B.[Bin],
Li, X.S.[Xian-Sheng],
Liu, H.X.[Hong-Xing],
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Synthetic aperture radar, Image understanding, Ship detection,
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IEEE DOI
2003
Marine vehicles, Feature extraction, Real-time systems,
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CNN
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Maritime traffic service networks,
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2007
Marine vehicles, Feature extraction, Proposals, Object detection,
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Biological system modeling, Adaptation models,
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2012
Marine vehicles, Accidents, Predictive models, Collision avoidance,
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2012
Marine vehicles, Radar polarimetry, Object detection,
Feature extraction, Synthetic aperture radar, Semantics,
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2012
Marine vehicles, Feature extraction, Remote sensing, Proposals,
Object detection, Optical imaging, Optical sensors,
ship detection
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2101
Target tracking, Radar tracking, Marine vehicles, Proposals,
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ICIP18(1328-1332)
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IEEE DOI
1803
Convolution, Feature extraction, Marine vehicles, Object detection,
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Harbour pattern of life analysis with time series of medium
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IEEE DOI
1712
remote sensing, Erdas imagine environment, Harbour Pattern,
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ship detection
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1708
Complexity theory, Image segmentation, Imaging, Marine vehicles,
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1611
Detectors
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A Novel Ship Detection Method For Large-scale Optical Satellite Images
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AIPR15(1-8)
IEEE DOI
1605
aerospace instrumentation
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IEEE DOI
1512
SAR
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AVSS15(1-6)
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1511
infrared imaging
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IEEE DOI
1510
Cameras
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IPTA14(1-6)
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1503
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DICTA14(1-6)
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feature extraction
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image denoising
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