Revisions to the JDL data fusion model

By A. Steinberg, C. Bowman, F. White. 1999

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Citations in the corpus

A survey of data fusion in smart city applications (2019, methodology): “We use smart city single perspective data fusion review papers [19], [26] and non-smart city data fusion classiﬁcation papers [18], [39]– [41] as references.”
Watchdog Agent - an infotronics-based prognostics approach for product performance degradation assessment and prediction (2003, methodology): “Following nomenclature defined by the JDL standard for sensor and data fusion [27], Watchdog Agents perform sensor fusion at the decision-level [10] or feature-level [12–14,16–19].”
Ontology-based situation awareness (2009, background): “In this section, we identify and discuss some of the most common interpretations of this concept and relate them both to the JDL Data Fusion Model [28] and to the model of Endsley [3].”
Multi-sensor management for information fusion: issues and approaches (2002, methodology): “As a categorization of process reﬁnement, Steinberg and Bowman [68] classiﬁed responses of resources (including sensors) as reﬂexive , feature-based , entity-relation based , context-sensitive , cost-sensitive , and re-action-sensitive , in terms of input data/information types.”
Revisiting the JDL Data Fusion Model II (2004, methodology): “As properly pointed out in [1], dat a association and assignment is occurring within each Level of the JDL Model, although the JDL diagrammatic structure of Fig.”
Data fusion in intelligent transportation systems: Progress and challenges - A survey (2011, background): “It may normalize, format, order, batch, and compress input data [2,30].”
Multimodal machine learning in precision health: A scoping review (2022, background): “Data fusion is underpinned by information theory and is the mechanism by which disparate data sources are merged to create an information state based on the sources ’ complementarity 15,16 (Box 1).”
Multisensor data fusion: A review of the state-of-the-art (2013, background): “Despite its popularity, the JDL model has many shortcomings, such as being too restrictive and especially tuned to military applications, which have been the subject of several extension proposals [13,14] attempting to alleviate them.”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, methodology): “Sensor fusion is the process of combing the data from multiple sensors to estimate the states of an object and achieve object detection and classiﬁcation [291], [292].”
A Survey on Trust Modeling (2015, methodology): “They show the data-feature-decision (DFD) model [Bedworth and Obrien 2000] for the machine fusion parts and the Joint Director’s of Labs (JDL) model [Steinberg et al. 1999] for the human–computer interfaces.”