In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is required for verification. A novel so...
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In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is required for verification. A novel solution is presented that makes use of active learning combined with an ensemble of classifiers for each class. The result is a significant reduction in required expert involvement for uncertain image region classification.
An ID recognition system is described that uses optical beacons and a high-speed image sensor. The ID sensor captures a scene like an ordinary camera and recognizes the ID of a beacon emitted over a long distance. The...
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ISBN:
(纸本)9780769520063
An ID recognition system is described that uses optical beacons and a high-speed image sensor. The ID sensor captures a scene like an ordinary camera and recognizes the ID of a beacon emitted over a long distance. The ID recognition system has three features. The system is robust to changes in the optical environment, e.g. complete darkness, spotlights, and sunlight. It can recognize up to 255 multiple optical beacons simultaneously. Furthermore, it can recognize beacons even over a long distance, e.g. 40 m indoors and 20 m outdoors. Implementation and evaluation of this ID recognition system showed that a mobile augmented reality system can be achieved by combining this ID recognition system with a PDA and a wireless network.
Recent advances in machine learning and pattern recognition methods provide new analytical tools to explore high dimensional gene expression microarray data. Our data mining software, VISual Data Analyzer for cluster ...
Recent advances in machine learning and pattern recognition methods provide new analytical tools to explore high dimensional gene expression microarray data. Our data mining software, VISual Data Analyzer for cluster discovery (VISDA), reveals many distinguishing patterns among gene expression profiles, which are responsible for the cell's phenotypes. The model-supported exploration of high-dimensional data space is achieved through two complementary schemes: dimensionality reduction by discriminatory data projection and cluster decomposition by soft data clustering. Reducing dimensionality generates the visualization of the complete data set at the top level. This data set is then partitioned into subclusters that can consequently be visualized at lower levels and if necessary partitioned again. In this paper, three different algorithms are evaluated in their abilities to reduce dimensionality and to visualize data sets: Principal Component Analysis (PCA), Discriminatory Component Analysis (DCA), and Projection Pursuit Method (PPM). The partitioning into subclusters uses the Expectation-Maximization (EM) algorithm and the hierarchical normal mixture model that is selected by the user and verified “optimally” by the Minimum Description Length (MDL) criterion. These approaches produce different visualizations that are compared against known phenotypes from the microarray experiments. Overall, these algorithms and user-selected models explore the high dimensional data where standard analyses may not be sufficient.
An ID recognition system is described that uses optical beacons and a high-speed image sensor. The ID sensor captures a scene like an ordinary camera and recognizes the ID of a beacon emitted over a long distance. The...
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＜正＞A framework is proposed for enterprise automated call routing system development and large scalable natural language call routing application deployment based on IBM’s speech recognition and NLU application eng...
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＜正＞A framework is proposed for enterprise automated call routing system development and large scalable natural language call routing application deployment based on IBM’s speech recognition and NLU application engagement practices in recently years. To facilitate employing different call classification algorithms in an easy integration manner,this framework architecture provides a plug ＆ play environment for evaluating promising call routing algorithms and a systematic approach to carry out a large scalable enterprise application deployment. The paradigm in this paper illustrates the complementary effort to develop an automatic call routing application for enterprise call centers and covers from call classification algorithm investigation to application programming model. Experimental results on a live data testing set collected from an enterprise call center shows that the performance of the call classification algorithm implemented in this framework is outstanding.
The article discusses an autonomous robot for the AAAI Robot Challenge. In an attempt to solve as much of the AAAI Robot Challenge as possible, five research institutions representing academia, industry and government...
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The article discusses an autonomous robot for the AAAI Robot Challenge. In an attempt to solve as much of the AAAI Robot Challenge as possible, five research institutions representing academia, industry and government integrated their research into a single robot named Grace. The article describes the first-year effort by the Grace team, including not only the various techniques each participant brought to Grace but also the difficult integration effort itself.
The combination of an interactive large screen display and wireless handheld devices in a meeting room setting can augment and enhance collaborative activities. This work examines the issues in developing applications...
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ISBN:
(纸本)1581134541
The combination of an interactive large screen display and wireless handheld devices in a meeting room setting can augment and enhance collaborative activities. This work examines the issues in developing applications to support such a collaborative meeting place.
User interfaces can improve task performance by exploiting the powerful human capabilities for spatial cognition. This opportunity has been demonstrated by many prior experiments. It is tempting to believe that provid...
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ISBN:
(纸本)1581134533
User interfaces can improve task performance by exploiting the powerful human capabilities for spatial cognition. This opportunity has been demonstrated by many prior experiments. It is tempting to believe that providing greater spatial flexibility-by moving from flat 2D to 3D user interfaces-will further enhance user performance. This paper describes an experiment that investigates the effectiveness of spatial memory in real-world physical models and in equivalent computer-based virtual systems. The different models vary the user's freedom to use depth and perspective in spatial arrangements of images representing web pages. Results show that the subjects' performance deteriorated in both the physical and virtual systems as their freedom to locate items in the third dimension increased. Subjective measures reinforce the performance measures, indicating that users found interfaces with higher dimensions more 'cluttered' and less efficient.
Gesture based interfaces promise to increase the efficiency of user input, particularly in mobile computing where standard input devices such as the mouse and keyboard are impractical. This paper describes an investig...
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