Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression † [PDF]
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
doaj +3 more sources
What Is Machine Learning, Artificial Neural Networks and Deep Learning?-Examples of Practical Applications in Medicine. [PDF]
Diagnostics (Basel), 2023 Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained ...
Kufel J +13 more
europepmc +5 more sources
From artificial neural networks to deep learning for music generation: history, concepts and trends [PDF]
Neural Computing and Applications, 2020 The current wave of deep learning (the hyper-vitamined return of artificial neural networks) applies not only to traditional statistical machine learning tasks: prediction and classification (e.g., for weather prediction and pattern recognition), but has already conquered other areas, such as translation. A growing area of application is the generation
Jean-Pierre Briot
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Fundamentals of Artificial Neural Networks and Deep Learning [PDF]
, 2022 AbstractIn this chapter, we go through the fundamentals of artificial neural networks and deep learning methods. We describe the inspiration for artificial neural networks and how the methods of deep learning are built. We define the activation function and its role in capturing nonlinear patterns in the input data.
Osval A. Montesinos‐López +2 more
openalex +3 more sources
Deep Learning and Artificial Neural Networks for Spacecraft Dynamics, Navigation and Control
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
doaj +3 more sources
Traditional Artificial Neural Networks Versus Deep Learning in Optimization of Material Aspects of 3D Printing. [PDF]
Materials (Basel), 2021 Rojek I +5 more
europepmc +3 more sources
Passenger Screening using Deep Learning and Artificial Neural Networks
, 2019 In this research, we have to detect the contrabands hidden in the human body’s scanned images at airport security machines using segmentation and classification. Present algorithm of security scanning machines at the airports of USA are producing high rate of false negatives which in cases lead to engage in a secondary, manual screening process that ...
Sarthak Arora +2 more
openalex +4 more sources
Bio-Inspired Neural Network Dynamics-Aware Reinforcement Learning for Spiking Neural Network [PDF]
BiomimeticsArtificial Intelligence (AI) has seen rapid advancements in recent times, finding applications across various sectors and achieving notable successes. However, current AI models based on Deep Convolutional Neural Networks (DNNs) face numerous challenges,
Yu Zheng +3 more
doaj +2 more sources
DiagnosticsDeep learning has revolutionised medical image analysis, offering the possibility of automated, efficient, and highly accurate diagnostic solutions. This article explores recent developments in deep learning techniques applied to medical imaging, including convolutional neural networks (CNNs) for classification and segmentation, recurrent neural ...
Olamilekan Shobayo, Reza Saatchi
openalex +5 more sources
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
doaj +1 more source