Maritime anomaly detection: A review
暂无分享,去创建一个
[1] Allen M. Waxman,et al. SeeCoast: persistent surveillance and automated scene understanding for ports and coastal areas , 2007, SPIE Defense + Commercial Sensing.
[2] Nelson F. F. Ebecken,et al. A SURVEY ON VIDEO DETECTION AND TRACKING OF MARITIME VESSELS , 2014 .
[3] Etienne Martineau,et al. Maritime Anomaly Detection: Domain Introduction and Review of Selected Literature , 2011 .
[4] Maarten van Someren,et al. Recognizing Vessel Movements from Historical Data , 2013, Situation Awareness with Systems of Systems.
[5] Cynthia Rudin,et al. Algorithms for interpretable machine learning , 2014, KDD.
[6] B.J. Rhodes,et al. SeeCoast: Automated Port Scene Understanding Facilitated by Normalcy Learning , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.
[7] Dimitrios Zissis,et al. A cloud based architecture capable of perceiving and predicting multiple vessel behaviour , 2015, Appl. Soft Comput..
[8] D. Sperling,et al. Four routes to better maritime governance , 2016, Nature.
[9] Raffaele Grasso,et al. Fusion of AIS, RADAR, and SAR data for maritime surveillance , 2007, SPIE Remote Sensing.
[10] Melita Hadzagic,et al. Information Mining Technologies to Enable Discovery of Actionable Intelligence to Facilitate Maritime Situational Awareness: I-MINE , 2013 .
[11] Harm Greidanus,et al. The declining impact of piracy on maritime transport in the Indian Ocean: Statistical analysis of 5-year vessel tracking data , 2015 .
[12] David S. Ebert,et al. A visual analytics process for maritime response, resource allocation and risk assessment , 2014, Inf. Vis..
[13] Wen-Chih Peng,et al. RouteMiner: Mining Ship Routes from a Massive Maritime Trajectories , 2014, 2014 IEEE 15th International Conference on Mobile Data Management.
[14] John Stastny,et al. Enhanced ship detection from overhead imagery , 2008, SPIE Defense + Commercial Sensing.
[15] Camossi Elena,et al. Development of a Web-Based Geographical Information System for Interactive Visualization and Analysis of Container Itineraries , 2014 .
[16] Stan Matwin,et al. Vessel route anomaly detection with Hadoop MapReduce , 2014, 2014 IEEE International Conference on Big Data (Big Data).
[17] Rikard Laxhammar,et al. Anomaly detection for sea surveillance , 2008, 2008 11th International Conference on Information Fusion.
[18] Aldo Napoli,et al. Toward User-Centred Geovisual Analytics in Maritime Surveillance , 2013 .
[19] Michele Vespe,et al. Traffic knowledge discovery from AIS data , 2013, Proceedings of the 16th International Conference on Information Fusion.
[20] Lily Rachmawati,et al. Exploiting AIS Data for Intelligent Maritime Navigation: A Comprehensive Survey From Data to Methodology , 2016, IEEE Transactions on Intelligent Transportation Systems.
[21] Jurgen Beyerer,et al. Evaluation and comparison of anomaly detection algorithms in annotated datasets from the maritime domain , 2015, 2015 SAI Intelligent Systems Conference (IntelliSys).
[22] Øystein Helleren,et al. Operator and User Perspective of Fractionated AIS Satellite Systems , 2013 .
[23] Paolo Braca,et al. Detection of malicious AIS position spoofing by exploiting radar information , 2013, Proceedings of the 16th International Conference on Information Fusion.
[24] Nikos Pelekis,et al. Online event recognition from moving vessel trajectories , 2016, GeoInformatica.
[25] Rikard Laxhammar,et al. Anomaly Detection in Trajectory Data for Surveillance Applications , 2011 .
[26] Branko Ristic,et al. Detecting Anomalies from a Multitarget Tracking Output , 2014, IEEE Transactions on Aerospace and Electronic Systems.
[27] Kevin R. Keane. Detecting motion anomalies , 2017, IWGS@SIGSPATIAL.
[28] Aldo Napoli,et al. High-Level Taxonomy of Geovisual Analytics Tasks for Maritime Surveillance , 2013 .
[29] Kevin B. Korb,et al. Anomaly detection in vessel tracks using Bayesian networks , 2014, Int. J. Approx. Reason..
[30] Shibin Parameswaran,et al. Evaluation of maritime object detection methods for full motion video applications using the PASCAL VOC Challenge framework , 2015, Electronic Imaging.
[31] Maria Riveiro,et al. Explanation Methods for Bayesian Networks : review and application to a maritime scenario , 2009 .
[32] Ross Graham. MDA Challenges for Operational Research and Analysis , 2009 .
[33] Xavier Lerouvreur,et al. Unsupervised extraction of knowledge from S-AIS data for maritime situational awareness , 2013, Proceedings of the 16th International Conference on Information Fusion.
[34] Christoffer Brax,et al. Anomaly detection in the surveillance domain , 2011 .
[35] Milena Stróżyna,et al. Architecture of Maritime Awareness System Supplied with External Information , 2016 .
[36] Fernandez Arguedas Virginia,et al. Unsupervised Maritime Pattern Analysis to Enhance Contextual Awareness , 2014 .
[37] Stelios C. A. Thomopoulos,et al. OCULUS SeaTM: integrated maritime surveillance platform , 2015, Defense + Security Symposium.
[38] Tom Ziemke,et al. Improving maritime anomaly detection and situation awareness through interactive visualization , 2008, 2008 11th International Conference on Information Fusion.
[39] Steven C. Boraz. Maritime Domain Awareness: Myths and Realities , 2009 .
[40] Vladimir Radu Avram. A spatio-temporal data representation framework with applications to anomaly detection in the maritime domain , 2012 .
[41] Aaron Hunter,et al. Belief modeling for maritime surveillance , 2009, 2009 12th International Conference on Information Fusion.
[42] Göran Falkman,et al. Interactive Visualization of Normal Behavioral Models and Expert Rules for Maritime Anomaly Detection , 2009, 2009 Sixth International Conference on Computer Graphics, Imaging and Visualization.
[43] Daniel A. Keim,et al. Human-centered machine learning through interactive visualization , 2016 .
[44] Michele Vespe,et al. Vessel Pattern Knowledge Discovery from AIS Data: A Framework for Anomaly Detection and Route Prediction , 2013, Entropy.
[45] Allen M. Waxman,et al. Associative Learning of Vessel Motion Patterns for Maritime Situation Awareness , 2006, 2006 9th International Conference on Information Fusion.
[46] Michael Borth,et al. Situation Awareness with Systems of Systems , 2013, Situation Awareness with Systems of Systems.
[47] Aldo Napoli,et al. ScanMaris : automatic detection of abnormal vessel behaviours , 2008 .
[48] Claudio Ferrari,et al. An Analysis of Shipping Agreements: The Cooperative Container Network , 2014 .
[49] Valentina Dragos. From Finding to Explaining: Information Retrieval to Support Maritime Anomaly Analysis , 2016, Int. J. Knowl. Syst. Sci..
[50] Michael J Hanna. Encounter Detection Using Visual Analytics to Improve Maritime Domain Awareness , 2015 .
[51] Hans Wehn,et al. Maritime Situation Analysis: A Multi-vessel Interaction and Anomaly Detection Framework , 2014, 2014 IEEE Joint Intelligence and Security Informatics Conference.
[52] Anne-Laure Jousselme,et al. Dissecting uncertainty-based fusion techniques for maritime anomaly detection , 2015, 2015 18th International Conference on Information Fusion (Fusion).
[53] Dario Tarchi,et al. AIS reception characterisation for AIS on/off anomaly detection , 2016, 2016 19th International Conference on Information Fusion (FUSION).
[54] Lauro Snidaro,et al. Fusing uncertain knowledge and evidence for maritime situational awareness via Markov Logic Networks , 2015, Inf. Fusion.
[55] Harm Greidanus,et al. SAR Image Quality Assessment and Indicators for Vessel and Oil Spill Detection , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[56] Jesús García,et al. Context-based Information Fusion: A survey and discussion , 2015, Inf. Fusion.
[57] Tom Ziemke,et al. VISAD: an interactive and visual analytical tool for the detection of behavioral anomalies in maritime traffic data , 2009, Defense + Commercial Sensing.
[58] Fabio Mazzarella,et al. Estimated Time of Arrival Using Historical Vessel Tracking Data , 2018, IEEE Transactions on Intelligent Transportation Systems.
[59] Namje Park,et al. A Requirement Analysis of Awareness-Based Vessel Traffic Service System for Maritime Safety , 2014 .
[60] Dimitrova Tatyana,et al. An Interactive Web-Based Geographical System in Assisting Location Matching Decisions , 2013 .
[61] Paolo Braca,et al. Context-enhanced vessel prediction based on Ornstein-Uhlenbeck processes using historical AIS traffic patterns: Real-world experimental results , 2014, 17th International Conference on Information Fusion (FUSION).
[62] Giuliana Pallotta,et al. Maritime Traffic Networks: From Historical Positioning Data to Unsupervised Maritime Traffic Monitoring , 2018, IEEE Transactions on Intelligent Transportation Systems.
[63] Leonid Portnoy,et al. Intrusion detection with unlabeled data using clustering , 2000 .
[64] Michael Davenport. Literature and Product Review of Visual Analytics for Maritime Awareness , 2009 .
[65] Maria Riveiro,et al. Evaluation of Normal Model Visualization for Anomaly Detection in Maritime Traffic , 2014, TIIS.
[66] Gao Shu,et al. Study of Automatic Anomalous Behaviour Detection Techniques for Maritime Vessels , 2017, Journal of Navigation.
[67] Egils Sviestins,et al. Rule-based situation assessment for sea surveillance , 2006, SPIE Defense + Commercial Sensing.
[68] Visualizing Anomalies and Traffic Rules in a Maritime Setting Using Potential Fields , 2014 .
[69] Valérie Lavigne. Interactive Visualization Applications for Maritime Anomaly Detection and Analysis , 2014 .
[70] A. Farina,et al. Over the horizon maritime surveillance capability of DVB-T based Passive Radar , 2014, 2014 11th European Radar Conference.
[71] B.J. Rhodes,et al. Maritime situation monitoring and awareness using learning mechanisms , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.
[72] Daniele Nardi,et al. Enhancing Automatic Maritime Surveillance Systems With Visual Information , 2017, IEEE Transactions on Intelligent Transportation Systems.
[73] Richard O. Lane,et al. Maritime anomaly detection and threat assessment , 2010, 2010 13th International Conference on Information Fusion.
[74] Fabio Mazzarella,et al. Discovering vessel activities at sea using AIS data: Mapping of fishing footprints , 2014, 17th International Conference on Information Fusion (FUSION).
[75] Ashutosh Kumar Singh,et al. Coastal surveillance in multi sensor environment: A design approach , 2016, 2016 3rd International Conference on Recent Advances in Information Technology (RAIT).
[76] Cyril Ray,et al. Spatio-temporal visualisation of outliers , 2011 .
[77] Bengt Carlsson,et al. Learning Maritime Traffic Rules Using Potential Fields , 2015, ICCL.
[78] Josef Kittler,et al. Maritime anomaly detection in ferry tracks , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[79] Göran Falkman,et al. Supporting the Analytical Reasoning Process in Maritime Anomaly Detection: Evaluation and Experimental Design , 2010, 2010 14th International Conference Information Visualisation.
[80] Po-Ruey Lei,et al. A framework for anomaly detection in maritime trajectory behavior , 2015, Knowledge and Information Systems.
[81] Fabrizio Natale,et al. Mapping Fishing Effort through AIS Data , 2015, PloS one.
[82] Jarke J. van Wijk,et al. Eurographics/ Ieee-vgtc Symposium on Visualization 2009 Visualization of Vessel Movements , 2022 .
[83] Göran Falkman,et al. Anomaly detection in sea traffic - A comparison of the Gaussian Mixture Model and the Kernel Density Estimator , 2009, 2009 12th International Conference on Information Fusion.
[84] Jean Roy,et al. Exploitation of maritime domain ontologies for anomaly detection and threat analysis , 2010, 2010 International WaterSide Security Conference.
[85] B.J. Rhodes,et al. Adaptive spatial scale for cognitively-inspired motion pattern learning & analysis algorithms for higher-level fusion and automated scene understanding , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.
[86] Daniel A. Keim,et al. Mastering the Information Age - Solving Problems with Visual Analytics , 2010 .
[87] Carlos Guestrin,et al. "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.
[88] Dario Tarchi,et al. Radiolocation and tracking of automatic identification system signals for maritime situational awareness , 2015 .
[89] M. Sciotti,et al. Multi-sensor autonomous tracking for Maritime Surveillance , 2008, 2008 International Conference on Radar.
[90] Aldo Napoli,et al. Exploiting the Potential of the Future “Maritime Big Data” , 2016 .
[91] Sangkyum Kim,et al. ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets , 2007, SDM.
[92] Mark R. Morelande,et al. Statistical analysis of motion patterns in AIS Data: Anomaly detection and motion prediction , 2008, 2008 11th International Conference on Information Fusion.
[93] Stéphane Bressan,et al. ASSIST: access controlled ship identification streams , 2011, Trans. Large Scale Data Knowl. Centered Syst..
[94] Jochen Horstmann,et al. Evaluation of an HF-radar ship detection and tracking algorithm by comparison to AIS and SAR data , 2010, 2010 International WaterSide Security Conference.
[95] Natalie Fridman,et al. KINGFISHER: Total Maritime Awareness System , 2017, AAMAS.
[96] C. Ducruet. Maritime Networks : Spatial structures and time dynamics , 2015 .
[97] Aldo Napoli,et al. Guiding the Controller in Geovisual Analytics to Improve Maritime Surveillance , 2013 .
[98] Paulo Vicente,et al. Maritime Domain Awareness , 2006 .
[99] Fabrizio Cuccoli,et al. Analysis of the radar coverage provided by a maritime Radar Network of Co-operative Vessels based on real AIS data , 2013, 2013 European Radar Conference.
[100] Kevin B. Korb,et al. Learning Abnormal Vessel Behaviour from AIS Data with Bayesian Networks at Two Time Scales , 2010 .
[101] Ke Wang,et al. Contextual verification for false alarm reduction in maritime anomaly detection , 2015, 2015 IEEE International Conference on Big Data (Big Data).
[102] J.W.F. Wiersma,et al. Assessing Vessel Traffic Service Operator Situation Awareness , 2010 .
[103] David S. Ebert,et al. TraSeer: A visual analytics tool for vessel movements in the coastal areas , 2017, 2017 IEEE International Symposium on Technologies for Homeland Security (HST).
[104] Ewa Osekowska,et al. Design and implementation of a maritime traffic modeling and anomaly detection method , 2014 .
[105] Miriam A. M. Capretz,et al. Contextual anomaly detection framework for big sensor data , 2015, Journal of Big Data.
[106] Aungon Nag Radon. False alarm reduction in maritime anomaly detection with contextual verification , 2015 .
[107] Anders Brödje. Hello, is there anybody out there – just nod if you can hear me , 2012 .
[108] Fabio Mazzarella,et al. Spatio-temporal data mining for maritime situational awareness , 2015, OCEANS 2015 - Genova.
[109] Maria Riveiro,et al. Visual analytics for maritime anomaly detection , 2011 .
[110] Jenna Burrell,et al. How the machine ‘thinks’: Understanding opacity in machine learning algorithms , 2016 .
[111] Aldo Napoli,et al. An enhanced spatial reasoning ontology for maritime anomaly detection , 2012, 2012 7th International Conference on System of Systems Engineering (SoSE).
[112] Anders Holst,et al. Incremental stream clustering and anomaly detection , 2008 .
[113] Tom Ziemke,et al. Reasoning about anomalies: a study of the analytical process of detecting and identifying anomalous behavior in maritime traffic data , 2009, Defense + Commercial Sensing.
[114] Jos van Hillegersberg,et al. Maritime pattern extraction and route reconstruction from incomplete AIS data , 2017, International Journal of Data Science and Analytics.
[115] Paolo Braca,et al. Maritime surveillance with multiple over-the-horizon HFSW radars: An overview of recent experimentation , 2015, IEEE Aerospace and Electronic Systems Magazine.
[116] Bradley J. Rhodes,et al. Probabilistic associative learning of vessel motion patterns at multiple spatial scales for maritime situation awareness , 2007, 2007 10th International Conference on Information Fusion.
[117] A. Khatkhate,et al. Modelling and system identification of an experimental apparatus for anomaly detection in mechanical systems , 2007 .
[118] Paolo Braca,et al. Application of the JPDA-UKF to HFSW radars for maritime situational awareness , 2012, 2012 15th International Conference on Information Fusion.
[119] B. E. White,et al. Case study: Maritime domain awareness , 2010, 2010 IEEE International Systems Conference.
[120] Leto Peel,et al. Maritime anomaly detection using Gaussian Process active learning , 2012, 2012 15th International Conference on Information Fusion.
[121] Kristin A. Cook,et al. Illuminating the Path: The Research and Development Agenda for Visual Analytics , 2005 .
[122] Hans Hiemstra. Defining a Balanced Maritime Safety and Security System , 2008 .
[123] Paula Savioja,et al. Challenges of developing the complex socio-technical system: realising the present, acknowledging the past, and envisaging the future of vessel traffic services. , 2007, Applied ergonomics.
[124] Dario Tarchi,et al. A novel anomaly detection approach to identify intentional AIS on-off switching , 2017, Expert Syst. Appl..
[125] Metin Balci,et al. Towards Global Maritime Domain Awareness - "Recent Developments and Challenges" , 2006, 2006 9th International Conference on Information Fusion.
[126] A. Vandecasteele,et al. Spatial ontologies for detecting abnormal maritime behaviour , 2012, 2012 Oceans - Yeosu.
[127] Allen M. Waxman,et al. Cognitively-Inspired Motion Pattern Learning & Analysis Algorithms for Higher-Level Fusion and Automated Scene Understanding , 2007, MILCOM 2007 - IEEE Military Communications Conference.
[128] Jarke J. van Wijk,et al. Visualization of Vessel Traffic , 2013, Situation Awareness with Systems of Systems.
[129] Aldo Napoli,et al. A semi-supervised learning framework based on spatio-temporal semantic events for maritime anomaly detection and behavior analysis , 2013 .
[131] Elena Camossi,et al. Visualization of Container Movements through a Web-Based Geographical Information System , 2013, 2013 European Intelligence and Security Informatics Conference.
[132] Van Wimersma Greidanus Herman,et al. Data Driven Contextual Knowledge from and for Maritime Situational Awareness , 2014 .
[133] Yi Ming Dai,et al. TACSA: A web-service based system for coastal surveillance and situational awareness , 2015, 2015 International Carnahan Conference on Security Technology (ICCST).
[134] Wen-Chih Peng,et al. ConflictFinder: Mining Maritime Traffic Conflict from Massive Ship Trajectories , 2017, 2017 18th IEEE International Conference on Mobile Data Management (MDM).
[135] Josh Harguess,et al. Sparsity-driven anomaly detection for ship detection and tracking in maritime video , 2015, Defense + Security Symposium.
[136] Denis Gouin,et al. Applicability of Visual Analytics to Defence and Security Operations , 2011 .
[137] Maya Cakmak,et al. Power to the People: The Role of Humans in Interactive Machine Learning , 2014, AI Mag..
[138] Maria Riveiro. The importance of visualization and interaction in the anomaly detection process , 2013 .
[139] Jean Roy,et al. Rule-based expert system for maritime anomaly detection , 2010, Defense + Commercial Sensing.
[140] Stan Matwin,et al. Ship movement anomaly detection using specialized distance measures , 2015, 2015 18th International Conference on Information Fusion (Fusion).
[141] Rikard Laxhammar,et al. Conformal prediction for distribution-independent anomaly detection in streaming vessel data , 2010, StreamKDD '10.
[142] James B. Kraiman,et al. Automated anomaly detection processor , 2002, SPIE Defense + Commercial Sensing.
[143] Alessandro Rossi,et al. Sun-glint false alarm mitigation in a maritime scenario , 2014, Security and Defence.
[144] Daniele Nardi,et al. Integrated Visual Information for Maritime Surveillance , 2015 .
[145] Alain Bouju,et al. DeAIS project: Detection of AIS spoofing and resulting risks , 2015, OCEANS 2015 - Genova.
[146] G. Galdorisi,et al. Bridging the Policy and Technology Gap : A Process to Instantiate Maritime Domain Awareness , 2005, Proceedings of OCEANS 2005 MTS/IEEE.
[147] Niklas Lavesson,et al. Open data for anomaly detection in maritime surveillance , 2013, Expert Syst. Appl..
[148] Tom Ziemke,et al. Extracting rules from expert operators to support situation awareness in maritime surveillance , 2008, 2008 11th International Conference on Information Fusion.
[149] Jean Roy,et al. Anomaly detection in the maritime domain , 2008, SPIE Defense + Commercial Sensing.
[150] VARUN CHANDOLA,et al. Anomaly detection: A survey , 2009, CSUR.
[151] Daniel Dahlmeier,et al. sRADAR : A Complex Event Processing and Visual Analytics System for Maritime Intelligence , 2016 .
[152] Luca Cazzanti,et al. Mining maritime vessel traffic: Promises, challenges, techniques , 2015, OCEANS 2015 - Genova.
[153] Per M. Gustavsson,et al. Signature-based activity detection based on Bayesian networks acquired from expert knowledge , 2009, 2009 12th International Conference on Information Fusion.
[154] Anne-Laure Jousselme,et al. Data-driven detection and context-based classification of maritime anomalies , 2015, 2015 18th International Conference on Information Fusion (Fusion).
[155] Véronique Malaisé,et al. An integrated approach for visual analysis of a multisource moving objects knowledge base , 2010, Int. J. Geogr. Inf. Sci..
[156] Léon J. M. Rothkrantz,et al. A surveillance system of a military harbour using an automatic identification system , 2013, CompSysTech '13.
[157] H. Griffiths,et al. Passive coherent location radar systems. Part 1: performance prediction , 2005 .