Results 91 to 100 of about 134,020 (300)
Superintelligent Deep Learning Artificial Neural Networks
, 2019 Activation Functions are crucial parts of the Deep Learning Artificial Neural Networks. From the Biological point of view, a neuron is just a node with many inputs and one output. A neural network consists of many interconnected neurons. It is a “simple” device that receives data at the input and provides a response. The function of
openaire +2 more sources
Safety Analysis of Deep Neural Networks
, 2021 Deep Neural Networks (DNNs) are popular machine learning models which have found successful application in many different domains across computer science.
Guidotti D.
core
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Advanced Functional Materials, EarlyView.Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Heliport Detection Using Artificial Neural Networks
, 2020 Automatic image exploitation is a critical technology for quick content analysis of high-resolution remote sensing images. The presence of a heliport on an image usually implies an important facility, such as military facilities.
Baseski, Emre
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Fiber‐Based Wearable Electronics as Adaptive Biointerfaces for Healthcare Applications
Advanced Functional Materials, EarlyView.Fiber‐based wearable electronics have been extensively studied as adaptive healthcare biointerfaces. In this review, we classify and introduce fiber‐based systems according to biointerface design, conductive materials, transduction mechanisms, and healthcare applications, and provide a perspective on their translation toward reliable, continuous ...
Sangwoo Hong +5 more
wiley +1 more source
Traditional Artificial Neural Networks Versus Deep Learning in Optimization of Material Aspects of 3D Printing. [PDF]
Materials (Basel), 2021 Rojek I +5 more
europepmc +1 more source
From Artificial Neural Networks to Deep Learning: A Research Survey
Journal of Physics: Conference Series, 2020 Abstract Deep learning (DL) is one of the hot topics in the field of artificial intelligence. As an extension of artificial neural network (ANN), deep learning models have more powerful learning and adaptation capabilities and they develop more and more rapidly.
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Learning with Artificial Neural Networks [PDF]
, 2018 In this thesis, we make two contributions in learning with artificial neural networks. Artificial neural networks have made great success in various challenging domains.
Zhang, Shangtong
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Advanced Functional Materials, EarlyView.Forming‐free epitaxial Pt/La0.5Sr0.5CoOx (LSCO)/La0.5Sr0.5MnO3 (LSMO) memristors exhibit heterogeneous and partially reversible topotactic switching involving brownmillerite (BM)‐, Grenier (GN)‐like‐, and perovskite (PV)‐like configurations. Atomic‐resolution scanning transmission electron microscopy and in situ transmission electron microscopy resolve
Zi‐Qin Hong +5 more
wiley +1 more source
HeliyonThe use of MRI analysis for BTD and tumor type detection has considerable importance within the domain of machine vision. Numerous methodologies have been proposed to address this issue, and significant progress has been achieved in this domain via the ...
Jianhong Ye +5 more
doaj +1 more source