Results 51 to 60 of about 7,675,115 (371)
Neural Networks, 2003 In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large
CIARAMELLA A. +12 more
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Boosting Neural Networks [PDF]
Neural Computation, 2000 Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, Ada Boost, has been applied with great success to several benchmark machine learning problems using mainly decision trees as base classifiers.
Schwenk, Holger, Bengio, Yoshua
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ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020 In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural networks which are all trained jointly for the task of communicating correlated sources through a network of noisy point ...
Liu, Litian +3 more
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A survey of the recent architectures of deep convolutional neural networks [PDF]
Artificial Intelligence Review, 2019 Deep Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several competitions related to Computer Vision and Image Processing.
Asifullah Khan +3 more
semanticscholar +1 more source
Building a decoder of perceptual decisions from microsaccades and pupil size
Frontiers in Psychology, 2022 Many studies have reported neural correlates of visual awareness across several brain regions, including the sensory, parietal, and frontal areas. In most of these studies, participants were instructed to explicitly report their perceptual experience ...
Ryohei Nakayama +8 more
doaj +1 more source
On the Robustness of a Neural Network [PDF]
2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS), 2017 36th IEEE International Symposium on Reliable Distributed Systems 26 - 29 September 2017.
El Mhamdi, El Mahdi +2 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Frontiers in Human Neuroscience, 2019 The purpose of this study is to clarify whether there is a learning effect on brain activity after writing with an ink pen vs. a digital pen. Previous studies have reported the superiority of handwriting to typing in terms of learning performance, but ...
Kiyoyuki Osugi +7 more
doaj +1 more source
Olfactory Stimulation Modulates Visual Perception Without Training
Frontiers in Neuroscience, 2021 Considerable research shows that olfactory stimulations affect other modalities in high-level cognitive functions such as emotion. However, little known fact is that olfaction modulates low-level perception of other sensory modalities.
Yoshiaki Tsushima +2 more
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Scientific Reports, 2021 The most promising way to prevent the explosive spread of COVID-19 infection is to achieve herd immunity through vaccination. It is therefore important to motivate those who are less willing to be vaccinated. To address this issue, we conducted an online
Toshiko Tanaka +3 more
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