Results 101 to 110 of about 7,675,115 (371)
Neural Network Processing Neural Networks: An efficient way to learn higher order functions [PDF]
arXiv, 2019 Functions are rich in meaning and can be interpreted in a variety of ways. Neural networks were proven to be capable of approximating a large class of functions[1]. In this paper, we propose a new class of neural networks called "Neural Network Processing Neural Networks" (NNPNNs), which inputs neural networks and numerical values, instead of just ...
arxiv
Building Compact and Robust Deep Neural Networks with Toeplitz Matrices [PDF]
arXiv, 2021 Deep neural networks are state-of-the-art in a wide variety of tasks, however, they exhibit important limitations which hinder their use and deployment in real-world applications. When developing and training neural networks, the accuracy should not be the only concern, neural networks must also be cost-effective and reliable.
arxiv
Aging and Cancer, EarlyView.Aging weakens the blood–brain barrier (BBB), increasing susceptibility to CNS cancers and complicating treatment. This review examines BBB deterioration, its impact on drug delivery, and potential interventions like targeting neuroinflammation and advanced therapies.
Quang La, Aiman Baloch, David F. Lo
wiley +1 more source
NeuroImage, 2022 The initial decrease in the blood oxygenation level-dependent (BOLD) signal reflects primary neuronal activity more than the later hemodynamic positive peak responses.
Toshiko Tanaka +3 more
doaj
Application of Neural Network in Optimization of Chemical Process [PDF]
arXiv, 2021 Artificial neural network (ANN) has been widely used due to its strong nonlinear mapping ability, fault tolerance and self-learning ability. This article summarizes the development history of artificial neural networks, introduces three common neural network types, BP neural network, RBF neural network and convolutional neural network, and focuses on ...
arxiv
Variability in neural networks
eLife, 2018 Experiments on neurons in the heart system of the leech reveal why rhythmic behaviors differ between individuals.
Daniel R Kick, David J Schulz
openaire +4 more sources
A review of artificial intelligence in brachytherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen +4 more
wiley +1 more source
Communications BiologyThe variability in brain function forms the basis for our uniqueness. Prior studies indicate smaller individual differences and larger inter-subject correlation (ISC) in sensorimotor areas than in the association cortex.
Tomoya Nakai +2 more
doaj +1 more source
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan +6 more
wiley +1 more source
Scientific ReportsMotor imagery is a higher-order cognitive brain function that mentally simulates movements without performing the actual physical one. Although motor imagery has attracted the interest of many researchers, and mental practice utilizing motor imagery has ...
Tomoya Furuta +3 more
doaj +1 more source