Results 1 to 10 of about 10,127 (114)
ReLU, Sparseness, and the Encoding of Optic Flow in Neural Networks [PDF]
SensorsAccurate self-motion estimation is critical for various navigational tasks in mobile robotics. Optic flow provides a means to estimate self-motion using a camera sensor and is particularly valuable in GPS- and radio-denied environments. The present study
Oliver W. Layton +2 more
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Direct construction of sparse suffix arrays with Libsais [PDF]
BMC BioinformaticsBackground Pattern matching is a fundamental challenge in bioinformatics, especially in the fields of genomics, transcriptomics and proteomics. Efficient indexing structures, such as suffix arrays, are critical for searching large datasets.
Simon Van de Vyver +4 more
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Sparseness facilitates image encoding across visuo-frontal networks in freely moving macaque [PDF]
Nature CommunicationsSparseness is a quantitative measure of coding efficiency that characterizes the extent to which information is represented by the selective activation of a small subset of neurons.
Arun Parajuli +2 more
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Long memory lifetimes require complex synapses and limited sparseness
Frontiers in Computational Neuroscience, 2007 Theoretical studies have shown that memories last longer if the neural representations are sparse, that is, when each neuron is selective for a small fraction of the events creating the memories.
Stefano Fusi, Fusi Stefano
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Weighted Sparseness-Based Anomaly Detection for Hyperspectral Imagery
Sensors, 2023 Anomaly detection of hyperspectral remote sensing data has recently become more attractive in hyperspectral image processing. The low-rank and sparse matrix decomposition-based anomaly detection algorithm (LRaSMD) exhibits poor detection performance in ...
Zhen Zheng, Erwei Zhao, Xing Lian
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Frontiers in Applied Mathematics and StatisticsTemporal text data, such as news articles or Twitter feeds, often comprises a mixture of long-lasting trends and transient topics. Effective topic modeling strategies should detect both types and clearly locate them in time.
Deanna Needell
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Dissipativity Analysis of Large-Scale Networked Systems
Applied Sciences, 2023 This paper investigates the dissipativity analysis of large-scale networked systems with linear time-invariant dynamics. The networked system is composed of a large number of subsystems whose connections are arbitrary, and each subsystem can have ...
Yuanfei Sun, Jirong Wang, Huabo Liu
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Drones, 2023 In this paper, we address the challenge of low recognition rates in existing methods for radar signals from unmanned aerial vehicles (UAV) with low signal-to-noise ratios (SNRs).
Xuemin Liu +5 more
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Lifelong Learning Augmented Short Text Stream Clustering Method
IEEE Access, 2021 Depending on the scanning mode, existing short text stream clustering methods can be divided into the following two kinds of methods: one-pass-based and batch-based.
Jipeng Qiang +4 more
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Sensors, 2021 In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle
Yehao Ma +5 more
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