Results 31 to 40 of about 379,828 (307)
Natural and Projectively Invariant Quantizations on Supermanifolds [PDF]
, 2011 The existence of a natural and projectively invariant quantization in the sense of P. Lecomte [Progr. Theoret. Phys. Suppl. (2001), no. 144, 125-132] was proved by M. Bordemann [math.DG/0208171], using the framework of Thomas-Whitehead connections.
Leuther, Thomas, Radoux, Fabian
core +4 more sources
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
doaj +1 more source
Sensors, 2018 Spectrum sensing remains a challenge in the context of cognitive radio networks (CRNs). Compared with traditional single-user sensing, cooperative spectrum sensing (CSS) exploits multiuser diversity to overcome channel fading, shadowing, and hidden ...
Yuanhua Fu, Fan Yang, Zhiming He
doaj +1 more source
Learning Sparse Low-Precision Neural Networks With Learnable Regularization
IEEE Access, 2020 We consider learning deep neural networks (DNNs) that consist of low-precision weights and activations for efficient inference of fixed-point operations.
Yoojin Choi +2 more
doaj +1 more source
GHN-QAT: Training Graph Hypernetworks to Predict Quantization-Robust Parameters of Unseen Limited Precision Neural Networks [PDF]
arXiv, 2023 Graph Hypernetworks (GHN) can predict the parameters of varying unseen CNN architectures with surprisingly good accuracy at a fraction of the cost of iterative optimization. Following these successes, preliminary research has explored the use of GHNs to predict quantization-robust parameters for 8-bit and 4-bit quantized CNNs.
arxiv
About its own time and the mass of the universe
St. Petersburg Polytechnical University Journal: Physics and Mathematics, 2021 A modification of the quantum theory of gravity in the case of a closed universe, in which the dynamics is reduced to the motion in the orbit of a group of general covariance, is proposed.
Gorobey Natalia +2 more
doaj +1 more source
Sensors, 2014 Compressive Sensing Imaging (CSI) is a new framework for image acquisition, which enables the simultaneous acquisition and compression of a scene. Since the characteristics of Compressive Sensing (CS) acquisition are very different from traditional image
Xiangwei Li +4 more
doaj +1 more source
Convolution Smooth: A Post-Training Quantization Method for Convolutional Neural Networks
IEEE AccessConvolutional neural network (CNN) quantization is an efficient model compression technique primarily used for accelerating inference and optimizing resources.
Yongyuan Chen, Zhendao Wang
doaj +1 more source
Advanced Functional Materials, EarlyView.A materials and device design concept that comprises a self‐assembled ultra‐thin epitaxial ion‐transporting layer, an amorphous oxide overcoat oxygen‐blocking layer, and a partial filament formed during an electroforming step is proposed for low‐current multilevel resistive switching devices.
Ming Xiao +17 more
wiley +1 more source
Generalized residual vector quantization for large scale data
, 2016 Vector quantization is an essential tool for tasks involving large scale data, for example, large scale similarity search, which is crucial for content-based information retrieval and analysis.
Liu, Shicong, Lu, Hongtao, Shao, Junru
core +1 more source