The need for fast and accurate text entry on small handheld computers has led to a resurgence of interest in on-line word recognition using artificial neural networks. Classical methods have been combined and improved...
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The need for fast and accurate text entry on small handheld computers has led to a resurgence of interest in on-line word recognition using artificial neural networks. Classical methods have been combined and improved to produce robust recognition of hand-printed English text. The central concept of a neural net as a character classifier provides a good base for a recognition system; long-standing issues relative to training generalization, segmentation, probabilistic formalisms, etc., need to resolved, however, to get adequate performance. A number of innovations in how to use a neural net as a classifier in a word recognizer are presented: negative training, stroke warping, balancing, normalized output error, error emphasis, multiple representations, quantized weights, and integrated word segmentation all contribute to efficient and robust performance.
Workstations and personal computers are increasingly being delivered with the ability to handle multimedia data;more and more of us are linked by high-speed digital networks. With multimedia communication environments...
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KidSim is an environment that allows children to create their own simulations. They create their own characters, and they create rules that specify how the chammters are to behave and interact. KidSim is programmed by...
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Manipulating programs is hard, while manipulating objects in the physical world is often easy. Several attributes of the physical world help make it comprehensible and manipulable: concreteness, uniformity, and flexib...
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Advancements in storage technology along with the fast deployment of high-speed networks has allowed the storage, transmission and manipulation of multimedia information such as text, graphics, still images, video and...
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Advancements in storage technology along with the fast deployment of high-speed networks has allowed the storage, transmission and manipulation of multimedia information such as text, graphics, still images, video and audio to be feasible. Our study focused on, the performance of the mass storage system for a large-scale video-on-demand server. Different video file striping schemes, such as application level striping and device driver level striping, were examined in order to study scalability and performance issues. To study the impact of different concurrent access patterns on the performance of a server, experimental results were obtained on group access on a single video file and multiple group accesses on multiple video files.
Video and audio conferencing over networks is becoming increasingly popular due to the availability of video and audio I/O as standard equipment on many computer systems. So far, many algorithms have concentrated on p...
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Video and audio conferencing over networks is becoming increasingly popular due to the availability of video and audio I/O as standard equipment on many computer systems. So far, many algorithms have concentrated on playback only capability. This generally results in unacceptable real-time performance with respect to latency and encoder complexity. We describe a software-only system that allows full duplex video communication. For our analysis and implementation we chose a DCT based method that uses motion estimation and is modelled on the CCITT H.261 standard. We discuss the algorithm, followed by an analysis of the computational requirements for each major block. The results presented show the effect of computational simplifications on signal to noise ratio and image quality. We also examine the processing needs for full resolution coding and project when this will become available.
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