Jaroslaw Marek

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  • Francisco J Dõ Âez, Spain Madrid, J Marek, Druzdzel
  • 2002
Most artificial intelligence applications, especially expert systems, have to reason and make decisions based on uncertain data and uncertain models. For this reason, several methods have been proposed for reasoning with different kinds of uncertainty. INTRODUCTION We often have to make decisions based on uncertain knowledge, not only in our private lives(More)
Firstly the paper reports experimental results proving that Cascaded Pixel Domain Transcoder (CPDT) is extremely inefficient when used for AVC/H.264 bitstream transcoding aimed at bitrate reduction not exceeding 30% of primary bitrate. In the paper, proposed is a transcoder that exploits structured truncation of bitsream and an algorithm for such truncation(More)
The paper deals with transcoding of AVC/H.264 bitstreams where some bitrate reduction is required. For single-layer bitstreams, often Cascaded Pixel Domain Transcoders (CPDT) are used unaware of the fact that such transcoders are complex and very inefficient when used for bitrate reduction not exceeding 30% of the primary bitrate. In order to avoid these(More)
This paper presents a semi-automated algorithm for accurate and reproducible segmentation of fiber-like objects. Novel features are introduced that effectively characterize fiber-like objects. The method is based on the classic live-wire algorithm, but two important innovations are suggested for decreasing user introduced bias: optimization of manually(More)
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