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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
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Construction of all even lengths type-II Z-complementary pair with a large zero-correlation zone
This paper presents a direct construction of type-II Z-complementary pair (ZCP) of q -ary ( q is even) for all even lengths with a wide...
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Sublinear Algorithms in T-Interval Dynamic Networks
We consider standard T - interval dynamic networks , under the synchronous timing model and the broadcast CONGEST model. In a T - interval dynamic network ,...
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Explicit constructions of NMDS self-dual codes
Near maximum distance separable (NMDS) codes are important in finite geometry and coding theory. Self-dual codes are closely related to...
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A mixture of experts regression model for functional response with functional covariates
Due to the fast growth of data that are measured on a continuous scale, functional data analysis has undergone many developments in recent years....
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Dynamic event-triggered adaptive control for state-constrained strict-feedback nonlinear systems with guaranteed feasibility conditions
In this paper, a new dynamic event-triggered control solution is presented for state-constrained strict-feedback nonlinear systems. The current...
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KHACDD: a knowledge-based hybrid method for multilabel sentiment analysis on complex sentences using attentive capsule and dual structured recurrent network
Using a machine to mine public opinion saves money and time. Traditional sentiment analysis approaches are typically unable to handle multi-meaning...
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A limit formula and a series expansion for the bivariate Normal tail probability
This work presents a limit formula for the bivariate Normal tail probability. It only requires the larger threshold to grow indefinitely, but...
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Classifier-dependent feature selection via greedy methods
The purpose of this study is to introduce a new approach to feature ranking for classification tasks, called in what follows greedy feature...