Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Geoff A. Gross"'
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 60:318-322
Qualitative linguistic data provides unique, valuable information that can only come from human observers. Data fusion systems find it challenging to incorporate this “soft data” as they are primarily designed to analyze quantitative, hard-sensor
Autor:
Geoff A. Gross, Rakesh Nagi
Publikováno v:
Information Fusion. 27:240-254
Presents method for modeling multiple situations of interest as single template graph.Enables precedence tree guidance of a graph matching (GM) search heuristic.Demonstrates significant speedup of the proposed AND/OR GM methodology.Performs numerous
Publikováno v:
Information Fusion. 21:130-144
This paper presents a framework for characterizing errors associated with different categories of human observation combined with a method for integrating these into a hard+soft data fusion system. Error characteristics of human observers (often refe
Publikováno v:
Information Fusion. 18:43-61
In intelligence analysis a situation of interest is commonly obscured by the more voluminous amount of unimportant data. This data can be broadly divided into two categories, hard or physical sensor data and soft or human observed data. Soft intellig
Publikováno v:
Context-Enhanced Information Fusion ISBN: 9783319289694
Context-Enhanced Information Fusion
Context-Enhanced Information Fusion
Source characterization is a fundamental function in fusion process design; this chapter addresses the issues involved when the characteristics of contextual information include uncertain and imprecise qualities and examines the associated impacts on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::194ce99226617d8cf32cf2d973f912d3
https://doi.org/10.1007/978-3-319-28971-7_3
https://doi.org/10.1007/978-3-319-28971-7_3
Publikováno v:
CogSIMA
This paper describes a mixed-initiative model of knowledge discovery capable of monitoring a dynamic environment, in which uncertain and unreliable messages can be reasoned over for recognizing human activities and predicting likely threats. The mode
Publikováno v:
Social Computing, Behavioral-Cultural Modeling, and Prediction ISBN: 9783319162676
SBP
SBP
This paper reports on the utility of social network analysis methods in the data fusion domain. Given fused data that combines multiple intelligence reports from the same environment, social network extraction and High Value Individual (HVI) identifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a63b946d36878ce0bf0364d5ed89ffd
https://doi.org/10.1007/978-3-319-16268-3_5
https://doi.org/10.1007/978-3-319-16268-3_5
Publikováno v:
Next-Generation Analyst II.
Intelligence analysis depends on data fusion systems to provide capabilities of detecting and tracking important objects, events, and their relationships in connection to an analytical situation. However, automated data fusion technologies are not ma
Publikováno v:
CogSIMA
Visua l estimations of target attributes in a realworld environment are highly context-dependent when the estimations are provided by human observers. For example, the accuracy of an individual estimating the age, height, or weight of another person
Soft information, dirty graphs and uncertainty representation/processing for situation understanding
Publikováno v:
FUSION
In conventional warfare as well as counter-insurgency (COIN) operations, the understanding of the situation is extremely vital to assure a sense of security. Intelligence in COIN is about people, and deployed units in the field are the best sources o