Results 41 to 50 of about 10,610,136 (340)
An n-Sigmoid Activation Function to Improve the Squeeze-and-Excitation for 2D and 3D Deep Networks
Electronics, 2023 The Squeeze-and-Excitation (SE) structure has been designed to enhance the neural network performance by allowing it to execute positive channel-wise feature recalibration and suppress less useful features.
Desire Burume Mulindwa, Shengzhi Du
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Qanun Medika: Jurnal Kedokteran Fakultas Kedokteran Universitas Muhammadiyah Surabaya, 2020 Background: The Mayer–Rokitansky–Kuster–Hauser (MRKH) syndrome is congenital malformation due to utero‐vaginal agenesis. For many years Dr Soetomo Hospital has been applying McIndoe technique using biomaterial amnion.
Uning Marlina +4 more
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Sensors, 2019 Since second-order statistics-based methods rely heavily on Gaussianity assumption and fractional lower-order statistics-based methods depend on a priori knowledge of non-Gaussian noise, there remains a void in wideband bistatic multiple-input/multiple ...
Li Li, Nicolas H. Younan, Xiaofei Shi
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Approximation by Superpositions of a Sigmoidal Function
Zeitschrift für Analysis und ihre Anwendungen, 2003 We generalize a result of B. Gao and Y. Xu [J. Math. Anal. Appl. 178 (1993) 221–226] concerning the approximation of functions of bounded variation by linear combinations of a fixed sigmoidal function to the class of functions of bounded f-variation. Also, in the case of one variable, a proposition of A. R. Barron [IEEE Trans. Inf. Theory 36 (1993) 930–
LEWICKI G, MARINO, Giuseppe
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REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
Journal of Clinical and Translational Science, 2023 REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a ...
Xinying Fang +8 more
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Approximation by superpositions of a sigmoidal function [PDF]
Mathematics of Control, Signals, and Systems, 1989 In this paper we demonstrate that finite linear combinations of compositions of a fixed, univariate function and a set ofaffine functionals can uniformly approximate any continuous function of n real variables with support in the unit hypercube; only mild conditions are imposed on the univariate function.
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Making Risk Minimization Tolerant to Label Noise [PDF]
, 2015 In many applications, the training data, from which one needs to learn a classifier, is corrupted with label noise. Many standard algorithms such as SVM perform poorly in presence of label noise.
Ghosh, Aritra +2 more
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Construction of Meyer Wavelet Using Fully Smooth Sigmiod Function
Journal of Harbin University of Science and Technology, 2019 In order to obtain better smooth effect in signal or image reconstruction, the regularity or continuous differentiability of wavelet must be increased as much as possible.
SHAO Yun-hong, DENG Cai-xia, HE Peng
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Window functions and sigmoidal behaviour of memristive systems [PDF]
International Journal of Circuit Theory and Applications, 2016 SummaryA common approach to model memristive systems is to include empirical window functions to describe edge effects and nonlinearities in the change of the memristance. We demonstrate that under quite general conditions, each window function can be associated with a sigmoidal curve relating the normalised time‐dependent memristance to the time ...
Georgiou, PS +3 more
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The approximation operators with sigmoidal functions
Computers & Mathematics with Applications, 2009 AbstractThe aim of this paper is to investigate the error which results from the method of approximation operators with logarithmic sigmoidal function. By means of the method of extending functions, a class of feed-forward neural network operators is introduced.
Feilong Cao, Zhixiang Chen
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