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This study compares five input devices (mouse, mousepen, traekball, stylus, and touchscreen) on a series of goal-directed tasks using a drawing program. Striking performance differences are found for the touchsereen when compared with a previous study using a standard, isolated, laboratory task. The study also looks at the impact of device to screen mapping(More)
  • A Hoecker, P Speckmayer, +39 authors Alexander Voigt@cern Ch
  • 2009
— In high-energy physics, with the search for ever smaller signals in ever larger data sets, it has become essential to extract a maximum of the available information from the data. Multivariate classification methods based on machine learning techniques have become a fundamental ingredient to most analyses. Also the multivariate classifiers themselves have(More)
This study compares seven input devices (mouse, touchsereen, two trackba.lls, mousepen, touchp@ and joystick) performing a star tracing task. Along with the device comparisons, the diffemtce between moving with the selector button pressed (dragging) or with the button released (pointing) is examined. Recent work has found that dragging is slower and more(More)
This paper presents an adaptive fuzzy logic algorithm for sensor fusion related to mapping the environment. The proposed algorithm deals with unknown a-priori sensory distributions and with asynchronous update of the sensors. Feedback is calculated every time, each logical sensor sends new data and is used to measure on-line the logical sensors(More)
Machine vision technologies hold the promise of enabling rapid and accurate fruit crop yield predictions in the field. The key to fulfilling this promise is accurate segmentation and detection of fruit in images of tree canopies. This paper proposes two new methods for automated counting of fruit in images of mango tree canopies, one using texture-based(More)
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