Browsing by Subject "Machine learning"

Now showing items 1-8 of 8

    • Data-driven detection and context-based classification of maritime anomalies 

      Pallotta, Giuliana; Jousselme, Anne-Laure (CMRE, 2019/06)
      Discovering anomalies at sea is one of the critical tasks of Maritime Situational Awareness (MSA) activities and an important enabler for maritime security operations. This paper proposes a data-driven approach to anomaly ...

    • Demystifying deep convolutional neural networks for sonar image classification 

      Williams, David P. (CMRE, 2019/06)
      Deep convolutional neural networks (CNNs) are developed to perform underwater target classification in synthetic aperture sonar (SAS) imagery. The deep networks are trained using a huge database of sonar data collected at ...

    • A document-based data model for large scale computational maritime situational awareness 

      Cazzanti, Luca; Millefiori, Leonardo; Arcieri, Gianfranco (CMRE, 2019/06)
      Computational Maritime Situational Awareness (MSA) supports the maritime industry, governments, and international organizations with machine learning and big data techniques for analyzing vessel traffic data available ...

    • Mining maritime vessel traffic: promises, challenges, techniques 

      Cazzanti, Luca; Pallotta, Giuliana (CMRE, 2019/06)
      This paper discusses machine learning and data mining approaches to analyzing maritime vessel traffic based on the Automated Information System (AIS). We review recent efforts to apply machine learning techniques to AIS ...

    • Multi-view SAS image classification using deep learning 

      Williams, David P.; Dugelay, Samantha (CMRE, 2017/11)
      A new approach is proposed for multi-view classification when sonar data is in the form of imagery and each object has been viewed an arbitrary number of times. An image-fusion technique is employed in conjunction with a ...

    • On adaptive modulation for low SNR underwater acoustic communications 

      Pelekanakis, Konstantinos; Cazzanti, Luca (CMRE, 2019/05)
      This paper deals with adaptive underwater acoustic (UWA) communications where the receiver must operate at low signal-to-noise ratios (SNRs). The proposed modem is equipped with a set of direct sequence spread spectrum ...

    • Proceedings of the Maritime Situational Awareness Workshop 2019 

      Jousselme, Anne-Laure; Braca, Paolo; Millefiori, Leonardo; De Rosa, Francesca; Zocholl, Maximilian; Uney, Murat; Iphar, Clément; Gaglione, Domenico; Soldi, Giovanni; Forti, Nicola; D'Afflisio, Enrica (CMRE, 2021-01)
      The Maritime Situational Awareness Workshop (MSAW) was held 08 - 10 October 2019 in Lerici, La Spezia (Italy). CMRE organized this workshop with the objective of fostering the crossfertilization of ideas from scientific ...

    • Underwater target classification in synthetic aperture sonar imagery using deep convolutional neural networks 

      Williams, David P. (CMRE, 2019/06)
      Deep convolutional neural networks are used to perform underwater target classification in synthetic aperture sonar (SAS) imagery. The deep networks are learned using a massive database of real, measured sonar data collected ...