Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

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  • Publication
    Are you sure? Prediction revision in automated decision-making
    ( 2021)
    Burkart, Nadia
    ;
    Robert, Sebastian
    ;
    Huber, Marco
    With the rapid improvements in machine learning and deep learning, decisions made by automated decision support systems (DSS) will increase. Besides the accuracy of predictions, their explainability becomes more important. The algorithms can construct complex mathematical prediction models. This causes insecurity to the predictions. The insecurity rises the need for equipping the algorithms with explanations. To examine how users trust automated DSS, an experiment was conducted. Our research aim is to examine how participants supported by an DSS revise their initial prediction by four varying approaches (treatments) in a between-subject design study. The four treatments differ in the degree of explainability to understand the predictions of the system. First we used an interpretable regression model, second a Random Forest (considered to be a black box [BB]), third the BB with a local explanation and last the BB with a global explanation. We noticed that all participants improved their predictions after receiving an advice whether it was a complete BB or an BB with an explanation. The major finding was that interpretable models were not incorporated more in the decision process than BB models or BB models with explanations.
  • Publication
    Situation responsive networking of mobile robots for disaster management
    ( 2014)
    Kuntze, Helge-Björn
    ;
    Frey, Christian W.
    ;
    Emter, Thomas
    ;
    Petereit, Janko
    ;
    Tchouchenkov, Igor
    ;
    Müller, Thomas
    ;
    Tittel, Martin
    ;
    Worst, Rainer
    ;
    Pfeiffer, Kai
    ;
    Walter, Moriz
    ;
    Rademacher, Sven
    ;
    Müller, Fabian
    If a natural disaster like an earthquake or an accident in a chemical or nuclear plant hits a populated area, rescue teams have to get a quick overview of the situation in order to identify possible locations of victims, which need to be rescued, and dangerous locations, hich need to be secured. Rescue forces must operate quickly in order to save lives, and they often need to operate in dangerous enviroments. Hence, robot-supported systems are increasingly used to support and accelerate search operations. The objective of the SENEKA concept is the situation responsive networking of various robots and sensor systems used by first responders in order to make the search for victims and survivors more quick and efficient. SENEKA targets the integration of the robot-sensor network into the operation procedures of the rescue teams. The aim of this paper is to inform on the objectives and first research results of the ongoing joint research project SENEKA.
  • Publication
    SENEKA - sensor network with mobile robots for disaster management
    ( 2012)
    Kuntze, Helge-Björn
    ;
    Frey, Christian W.
    ;
    Tchouchenkov, Igor
    ;
    Staehle, Barbara
    ;
    Rome, Erich
    ;
    Pfeiffer, Kai
    ;
    Wenzel, Andreas
    ;
    Wöllenstein, Jürgen
    Developed societies have a high level of preparedness for natural or man-made disasters. But such incidents cannot be completely prevented, and when an incident like an earthquake or an accident in a chemical or nuclear plant hits a populated area, rescue teams need to be employed. In such situations it is a necessity for rescue teams to get a quick overview of the situation in order to identify possible locations of victims that need to be rescued and dangerous locations that need to be secured. Rescue forces must operate quickly in order to save lives, and they often need to operate in dangerous environments. Hence, robot-supported systems are increasingly used to support and accelerate search operations. The objective of the SENEKA concept is to network the various robots and sensor systems used by first responders in order to make the search for victims and survivors more quick and efficient. SENEKA targets the integration of the robot-sensor network into the operation procedures of the rescue teams. The aim of this paper is to inform on the goals and first research results of the ongoing joint research project SENEKA.