Results 31 to 40 of about 1,409,223 (260)
Procedural Learning With Robust Visual Features via Low Rank Prior
IEEE Access, 2019 In order to apply a convolutional neural network (CNN) to unseen datasets, a common way is to train a CNN using a pre-trained model on a big dataset by fine-tuning it instead of starting from scratch.
Haifeng Li +5 more
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A Sparse Denoising-Based Super-Resolution Method for Scanning Radar Imaging
Remote Sensing, 2021 Scanning radar enables wide-range imaging through antenna scanning and is widely used for radar warning. The Rayleigh criterion indicates that narrow beams of radar are required to improve the azimuth resolution.
Qiping Zhang +4 more
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Sparse Subspace Clustering: Algorithm, Theory, and Applications [PDF]
, 2013 In many real-world problems, we are dealing with collections of high-dimensional data, such as images, videos, text and web documents, DNA microarray data, and more.
Elhamifar, Ehsan, Vidal, Rene
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Sparsely Activated Networks [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 10 pages, 5 figures, 4 algorithms, 4 tables, submission to IEEE Transactions on Neural Networks and Learning ...
Paschalis Bizopoulos +1 more
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Impact of Sparse and Dense Deployment of Nodes Under Different Propagation Models in Manets
Advances in Distributed Computing and Artificial Intelligence Journal, 2020 Mobile Ad-hoc Network (MANET) is the most emerging and fast-expanding technology in the last two decades. One of the major issues and challenging areas in MANET is the process of routing due to dynamic topologies and high mobility of mobile nodes.
Altaf Hussain +3 more
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Orbit Determination Using SLR Data for STSAT-2C:Short-arc Analysis [PDF]
Journal of Astronomy and Space Sciences, 2015 In this study, we present the results of orbit determination (OD) using satellite laser ranging (SLR) data for the Science and Technology Satellite (STSAT)-2C by a short-arc analysis.
Young-Rok Kim +3 more
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Local-Sample-Weighted Clustering Ensemble with High-Order Graph Diffusion
Mathematics, 2023 The clustering ensemble method has attracted much attention because it can improve the stability and robustness of single clustering methods. Among them, similarity-matrix-based methods or graph-based methods have had a wide range of applications in ...
Jianwen Gan, Yunhui Liang, Liang Du
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Scaling Law for Recovering the Sparsest Element in a Subspace [PDF]
, 2014 We address the problem of recovering a sparse $n$-vector within a given subspace. This problem is a subtask of some approaches to dictionary learning and sparse principal component analysis.
Demanet, Laurent, Hand, Paul
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Sparse discretization of sparse control problems [PDF]
PAMM, 2019 AbstractWe consider optimal control problems that inherit a sparsity structure, especially we look at problems governed by measure controls. Our goal is to achieve maximal sparsity on the discrete level. We use variational discretization of the control problems utilizing a Petrov‐Galerkin approximation of the state, which induces controls that are ...
Evelyn Herberg +2 more
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International Journal of Technology, 2020 Cancer is one of the leading causes of death, and the brain is one of the body’s cancer-prone organs. The early detection of brain tumors can reduce cancer risk, which is practically assisted and conducted using scanners such as computed ...
Hermawan Rahman Sholeh +2 more
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