450 research outputs found

    Coding Transparency in Object-Based Video

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    Design, Implementation, and Evaluation of a Point Cloud Codec for Tele-Immersive Video

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    Efficient Coding of Shape and Transparency for Video Objects

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    Error and Congestion Resilient Video Streaming over Broadband Wireless

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    In this paper, error resilience is achieved by adaptive, application-layer rateless channel coding, which is used to protect H.264/Advanced Video Coding (AVC) codec data-partitioned videos. A packetization strategy is an effective tool to control error rates and, in the paper, source-coded data partitioning serves to allocate smaller packets to more important compressed video data. The scheme for doing this is applied to real-time streaming across a broadband wireless link. The advantages of rateless code rate adaptivity are then demonstrated in the paper. Because the data partitions of a video slice are each assigned to different network packets, in congestion-prone wireless networks the increased number of packets per slice and their size disparity may increase the packet loss rate from buffer overflows. As a form of congestion resilience, this paper recommends packet-size dependent scheduling as a relatively simple way of alleviating the buffer-overflow problem arising from data-partitioned packets. The paper also contributes an analysis of data partitioning and packet sizes as a prelude to considering scheduling regimes. The combination of adaptive channel coding and prioritized packetization for error resilience with packet-size dependent packet scheduling results in a robust streaming scheme specialized for broadband wireless and real-time streaming applications such as video conferencing, video telephony, and telemedicine

    Un-debunking ordinary objects with the help of predictive processing

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    Preprint artykułu, który ukaże się w czasopiśmie: British Journal for the Philosophy of Science (ISSN 0007-0882) w 2021 roku.Debunking arguments aim to undermine common sense beliefs by showing that they are not explanatorily or causally linked to the entities they are purportedly about. Rarely are facts about the etiology of common sense beliefs invoked for the opposite aim, that is, to support the reality of entities that furnish our manifest image of the world. Here I undertake this sort of un-debunking project. My focus is on the metaphysics of ordinary physical objects. I use the view of perception as approximate Bayesian inference to show how representations of ordinary objects can be extracted from sensory input in a rational and truth-tracking manner. Drawing an analogy between perception construed as Bayesian hypothesis testing and scientific inquiry, I sketch out how some of the intuitions that traditionally inspired arguments for scientific realism also find application with regards to proverbial tables and chairs

    Genomics, “Discovery Science,” Systems Biology, and Causal Explanation: What Really Works?

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    Diverse and non-coherent sets of epistemological principles currently inform research in the general area of functional genomics. Here, from the personal point of view of a scientist with over half a century of immersion in hypothesis driven scientific discovery, I compare and deconstruct the ideological bases of prominent recent alternatives, such as “discovery science,” some productions of the ENCODE project, and aspects of large data set systems biology. The outputs of these types of scientific enterprise qualitatively reflect their radical definitions of scientific knowledge, and of its logical requirements. Their properties emerge in high relief when contrasted (as an example) to a recent, system-wide, predictive analysis of a developmental regulatory apparatus that was instead based directly on hypothesis-driven experimental tests of mechanism
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