„Neuronales Netz“
Suchergebnisse
1.000+ Treffer
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Datengetriebene Anpassung des Fixierungshorizonts – Ein Machine-Learning-Ansatz für das Materialmanagement
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Schallanalyse Neuronale Repräsentation des Hörvorgangs als Basis
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Neural Networks for solving Inverse Problems. Applications in Materials Science and Medical Imaging – Neural Networks for solving Inverse Problems. Applications in Materials Science and Medical Imaging
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Oscillatory computational networks based on coupled VO₂ oscillators via tunable thermal triggering
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Towards a meaningful integration of neural networks in computational solid mechanics
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Rechtsfolgen der Urheberrechtsverletzung bei generativer Künstlicher Intelligenz – Über die Möglichkeit des „Vergessens“ in Neuronalen Netzen
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Asymptotically Optimal Channel Estimation and Learning Suitable Compressive Sensing Matrices
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Deep Learning-basierte Optimierung der automatischen optischen Qualitätssicherung in einer Elektronik-Fertigung
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General-Purpose Optimization Through Information Maximization
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Exponential dissipativity criteria for generalized BAM neural networks with variable delays
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KKT condition-based smoothing recurrent neural network for nonsmooth nonconvex optimization in compressed sensing
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Praxiseinstieg Deep Learning – Mit Python, Caffe, TensorFlow und Spark eigene Deep-Learning-Anwendungen erstellen
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Simple speed estimators reproduce MT responses and identify strength of visual illusion
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Query-specific optimal convolutional neural ranker
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Improvement on projection twin support vector machine
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Smooth statistical modeling of bivariate non-monotonic data by a three-stage LUT neural system
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2D recurrent neural networks: a high-performance tool for robust visual tracking in dynamic scenes
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Development of novel methods to predict the strength properties of thermally treated sandstone using statistical and soft-computing approach
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An improved back propagation neural network based on complexity decomposition technology and modified flower pollination optimization for short-term load forecasting
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Accurate photovoltaic power forecasting models using deep LSTM-RNN