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Deep Learning and Artificial Neural Networks for Spacecraft Dynamics, Navigation and Control [PDF]
Drones, 2022 The growing interest in Artificial Intelligence is pervading several domains of technology and robotics research. Only recently has the space community started to investigate deep learning methods and artificial neural networks for space systems.
Stefano Silvestrini, Michèle Lavagna
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A Layer-Wise Theoretical Framework for Deep Learning of Convolutional Neural Networks
IEEE Access, 2022 As research attention in deep learning has been focusing on pushing empirical results to a higher peak, remarkable progress has been made in the performance race of machine learning applications in the past years.
Huu-Thiet Nguyen +2 more
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A Review of Deep Learning Algorithms and Their Applications in Healthcare
Algorithms, 2022 Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as
Hussein Abdel-Jaber +4 more
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On the relationship between predictive coding and backpropagation.
PLoS ONE, 2022 Artificial neural networks are often interpreted as abstract models of biological neuronal networks, but they are typically trained using the biologically unrealistic backpropagation algorithm and its variants.
Robert Rosenbaum
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Challenge of the performance management of trust control systems with deep learning
Advanced Engineering Research, 2022 Introduction. The significance of machine learning under the conditions of digital transformation of industry, and methods of implementing deep learning to provide the performance of trust management systems are considered.
A. A. Zelensky +4 more
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An Introduction to Neural Networks
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Neural networks ares an important type of machine learning that have generated significant interest due to their success on difficult problems.. This tutorial will provide an introduction and a high-level overview of artificial neural networks.
David Bisant
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The Limitations of Deep Learning in Achieving Real Artificial Intelligence
Proceedings, 2022 The achievement of artificial intelligence has been one of the goals in the field of machine learning, and achievements in the field of deep learning have led to the idea that the goal of so-called “intelligence” in artificial intelligence can be ...
Tianqi Wu, Ruiqi Jin
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Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression †
Energies, 2018 Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech ...
Gregory D. Merkel +2 more
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APL Machine Learning, 2023 The design and development of polymeric materials have been a hot domain for decades. However, traditional experiments and molecular simulations are time-consuming and labor-intensive, which no longer meet the requirements of new materials development ...
Dazi Li +5 more
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USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2017 This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Networks in impedance tomography. Machine Learning methods can be used to teach computers different technical problems.
Grzegorz Kłosowski, Tomasz Rymarczyk
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