Results 241 to 250 of about 77,307 (275)
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A class of probabilistic shape models
Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2002Deformable models are related to other data representation methods. It was recently proposed a class of models based on a fuzzy energy function which includes many well known algorithms (snakes, elastic nets, fuzzy and hard c-means and Kohonen maps). This paper describes a probabilistic extension of these algorithms in a Bayesian framework, using Gibbs-
J.S. Marques, A.J. Abrantes
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Probabilistic Shaping of Set-Partition mQAM
Optical Fiber Communication Conference (OFC) 2019, 2019We propose novel probabilistic shaping of set-partition mQAM signals to extend the entropy range below 2 bits/symbol and demonstrate a performance gain of 0.45dB compared to time-domain hybrid QAM at the same achievable information rate.
Inwoong Kim +3 more
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Probabilistic Aspects in Shape Memory Alloy Modelling
1998Shape-memory alloys (SMA) have potential for use in dissipation devices that are employed in the passive control of structural systems subjected to seismically induced vibration. The present paper extends to SMA an hysteretic constitutive law developed originally by Mroz for steel.
L. Faravelli, PETRINI, LORENZA
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Probabilistic Constellation Shaping: An Implementation Perspective
Optical Fiber Communication Conference (OFC) 2022, 2022This tutorial reviews recent advances in probabilistic constellation shaping (PCS) with particular focus on implementation perspectives. We analyze the complexity of several known shaping methods and discuss performance and complexity tradeoffs in different application scenarios.
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Experimental Demonstration of Probabilistically Shaped QAM
Advanced Photonics 2017 (IPR, NOMA, Sensors, Networks, SPPCom, PS), 2017We review the recent progress on probabilistically shaped QAM for high-performance optical transmission, and investigate into the receiver DSP for channel equalization.
Qian Hu +3 more
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Probabilistic Shaping for VCSEL-MMF Links
2018 IEEE Avionics and Vehicle Fiber-Optics and Photonics Conference (AVFOP), 2018We analyse the benefits of probabilistic shaping in reducing received power requirements in error-free VCSEL-MMF links. Experimental results demonstrate nearly 1 dB reduction for the same net data rate. All results are through 100m of OM5 fiber at 10−12 SER.
Siddharth Varughese +2 more
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Probabilistic shape vision for embedded systems
2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2011This paper presents a robust object tracking method using a sparse shape-based object model for embedded systems with limited computational capabilities. Our approach consists of three ingredients namely shapes, a motion model and a sparse (non-binary) sub-sampling of colours in background and foreground parts based on the shape assumption.
S. Olufs, M. Vincze, P. G. Ploger
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Probabilistic Fitting of Active Shape Models
2018Active Shape Models (ASMs) are a classical and widely used approach for fitting shape models to images. In this paper, we propose a fully probabilistic interpretation of ASM fitting as Bayesian inference. To infer the posterior, we use the Metropolis-Hastings algorithm. We then use the maximum a posteriori sample as the segmentation result.
Morel-Forster, Andreas +3 more
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Probabilistic shape descriptor for triangulated surfaces
IEEE International Conference on Image Processing 2005, 2005The importance of shape recognition is increasing rapidly in the field of computer graphics and multimedia communication because it is difficult to process information efficiently without its recognition. In this paper, we present a 3D object recognition approach based on a global geodesic measure. The key idea behind our methodology is to represent an
A.B. Hamza, H. Krim
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Bit-Level Probabilistically Shaped Coded Modulation
IEEE Communications Letters, 2017A routine to parallelize and increase the throughput of fixed length distribution matching with non-binary output alphabet is presented. The routine performs parallel distribution matchings with binary output alphabets, and then maps the binary output streams to symbols from the primary, non-binary alphabet.
Marcin Pikus, Wen Xu
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