Network

All posts under tag "Network"

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An Analog Neural Network Computing Engine using CMOS-Compatible Charge-Trap-Transistor (CTT)

An analog neural network computing engine based on CMOS-compatible charge-trap transistor (CTT) is proposed in this paper. CTT devices are used as analog multipliers. Compared to digital multipliers, CTT-based analog multiplier shows significant area and power reduction. The proposed computing engin

Network Machine Learning Emerging Technologies Hardware Architecture Computer Science
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Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models

In the last few years, we have seen the transformative impact of deep learning in many applications, particularly in speech recognition and computer vision. Inspired by Google's Inception-ResNet deep convolutional neural network (CNN) for image classification, we have developed 'Chemception', a deep

Computer Vision Computational Engineering Network Model Machine Learning Artificial Intelligence Computer Science Statistics
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End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks

Speech enhancement model is used to map a noisy speech to a clean speech. In the training stage, an objective function is often adopted to optimize the model parameters. However, in most studies, there is an inconsistency between the model optimization criterion and the evaluation criterion on the e

Network Machine Learning Computer Science Sound Statistics
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Mitigating Asymmetric Nonlinear Weight Update Effects in Hardware Neural Network based on Analog Resistive Synapse

Asymmetric nonlinear weight update is considered as one of the major obstacles for realizing hardware neural networks based on analog resistive synapses because it significantly compromises the online training capability. This paper provides new solutions to this critical issue through co-optimizati

Neural Computing Network Machine Learning Emerging Technologies Computer Science
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Network Community Detection: A Review and Visual Survey

Community structure is an important area of research. It has received a considerable attention from the scientific community. Despite its importance, one of the key problems in locating information about community detection is the diverse spread of related articles across various disciplines. To the

Detection Network Digital Libraries Computational Complexity Data Structures Computer Science Social Networks Discrete Mathematics
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On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems

Convolutional Neural Networks (CNNs) have shown a great deal of success in diverse application domains including computer vision, speech recognition, and natural language processing. However, as the size of datasets and the depth of neural network architectures continue to grow, it is imperative to

Network Distributed Computing System Computer Science
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Quantum walks on complex networks with connection instabilities and community structure

A continuous-time quantum walk is investigated on complex networks with the characteristic property of community structure, which is shared by most real-world networks. Motivated by the prospect of viable quantum networks, I focus on the effects of network instabilities in the form of broken links,

Condensed Matter Network Physics Computer Science Quantum Physics Social Networks
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Residue network in protein native structure belongs to the universality class of three dimensional critical percolation cluster

A single protein molecule is regarded as a contact network of amino-acid residues. Some studies have indicated that this network is a small world network (SWN), while other results have implied that this is a fractal network (FN). However, SWN and FN are essentially different in the dependence of th

Condensed Matter Network Physics Quantitative Biology
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Self-sustained asynchronous irregular states and Up/Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons

Randomly-connected networks of integrate-and-fire (IF) neurons are known to display asynchronous irregular (AI) activity states, which resemble the discharge activity recorded in the cerebral cortex of awake animals. However, it is not clear whether such activity states are specific to simple IF mod

Network Quantitative Biology
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Transparency guided ensemble convolutional neural networks for stratification of pseudoprogression and true progression of glioblastoma multiform

Pseudoprogression (PsP) is an imitation of true tumor progression (TTP) in patients with glioblastoma multiform (GBM). Differentiating them is a challenging and time-consuming task for radiologists. Although deep neural networks can automatically diagnose PsP and TTP, interpretability shortage is al

Network Quantitative Biology
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A stochastic model of human visual attention with a dynamic Bayesian network

Recent studies in the field of human vision science suggest that the human responses to the stimuli on a visual display are non-deterministic. People may attend to different locations on the same visual input at the same time. Based on this knowledge, we propose a new stochastic model of visual atte

Computer Vision Neural Computing Network Model Machine Learning Computer Science Multimedia Statistics
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Estimating and decomposing most productive scale size in parallel DEA networks with shared inputs: A case of Chinas Five-Year Plans

Attaining the optimal scale size of production systems is an issue frequently found in the priority questions on management agendas of various types of organizations. Determining the most productive scale size (MPSS) allows the decision makers not only to know the best scale size that their systems

Network Economics Quantitative Finance

< Category Statistics (Total: 5076) >

Electrical Engineering and Systems Science
104
General Relativity
64
General Research
786
HEP-EX
25
HEP-LAT
8
HEP-PH
82
HEP-TH
65
MATH-PH
74
NUCL-EX
6
NUCL-TH
14
Quantum Physics
65

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