Results 51 to 60 of about 298,825 (343)
Advances in Theoretical and Mathematical Physics, 2009 70 pp, v2: references ...
Gukov, Sergei, Witten, Edward
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Homotopy of rational maps and the quantization of Skyrmions [PDF]
, 2003 The Skyrme model is a classical field theory which models the strong interaction between atomic nuclei. It has to be quantized in order to compare it to nuclear physics.
Krusch, Steffen
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Computer Vision and Image Understanding, 2011 Vector quantization(VQ) is a lossy data compression technique from signal processing, which is restricted to feature vectors and therefore inapplicable for combinatorial structures. This contribution presents a theoretical foundation of graph quantization (GQ) that extends VQ to the domain of attributed graphs.
Brijnesh J. Jain, Klaus Obermayer
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Rate adaptive binary erasure quantization with dual fountain codes [PDF]
, 2008 —In this contribution, duals of fountain codes are introduced and their use for lossy source compression is investigated. It is shown both theoretically and experimentally that the source coding dual of the binary erasure channel coding problem, binary ...
Mohamed Ismail +8 more
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Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features
Data, 2018 In this paper, we propose an investigation of the properties of structural image recognition methods in the cluster space of characteristic features. Recognition, which is based on key point descriptors like SIFT (Scale-invariant Feature Transform), SURF
Oleksii Gorokhovatskyi +2 more
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Communication Efficient Federated Learning With Quantization-Aware Training Design
IEEE Transactions on Machine Learning in Communications and NetworkingModel quantization is an effective method that can improve communication efficiency in federated learning (FL). The existing FL quantization protocols almost stay at the level of post-training quantization (PTQ), which comes at the cost of large ...
Xiang Fang +4 more
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Evaluating Robustness to Noise and Compression of Deep Neural Networks for Keyword Spotting
IEEE Access, 2023 Keyword Spotting (KWS) has been the subject of research in recent years given the increase of embedded systems for command recognition such as Alexa, Google Home, and Siri. Performance, model size, processing time, and robustness to noise are fundamental
Pedro H. Pereira +2 more
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Sentinel-1 FDBAQ Performance Validation Using TerraSAR-X Data [PDF]
, 2012 Two Block Adaptive Quantization (BAQ) algorithms considered for implementation on-board Sentinel-1, the Entropy Constrained BAQ (ECBAQ) and the Flexible Dynamic BAQ (FDBAQ) are investigated with real data acquired by TerraSAR-X.
Evert Attema +9 more
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Nonlinear Quantization Method of SAR Images with SNR Enhancement and Segmentation Strategy Guidance
Remote SensingThe quantization process of synthetic aperture radar (SAR) images faces significant challenges due to their high dynamic range, resulting in notable quantization distortion.
Zijian Yao +3 more
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IEEE Access, 2023 As recent machine translation models are mostly based on the attention-based neural machine translation (NMT), many well-known models such as Transformer or bidirectional encoder representations from Transformers (BERT) have been proposed.
Mijin Go, Joonho Kong, Arslan Munir
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