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TERL: classification of transposable elements by convolutional neural networks
(2021-05-20)
Transposable elements (TEs) are the most represented sequences occurring in eukaryotic genomes. Few methods provide the classification of these sequences into deeper levels, such as superfamily level, which could provide ...
An adversarial model for paraphrase generation
(Universidad Católica San PabloPE, 2020)
Paraphrasing is the action of expressing the idea of a sentence using
different words. Paraphrase generation is an interesting and challenging
task due mainly to three reasons: (1) The nature of the text is discrete, ...
ConvolutionTR: comprehensive study of SNPs within tandem repeats.
(In: INTERNATIONAL PLANT & ANIMAL GENOME, 20., 2012, San Diego. Abstract... Jersey City: Scherago International, 2012., 2012)
Hypercyclic convolution operators on Fréchet spaces of analytic functions
(Academic Press Inc Elsevier Science, 2007-12)
A result of Godefroy and Shapiro states that the convolution operators on the space of entire functions on Cn, which are not multiples of identity, are hypercyclic. Analogues of this result have appeared for some spaces ...
On the approximation of compact fuzzy sets
(Pergamon-elsevier Science LtdOxfordInglaterra, 2011)
Two-Stage Human Activity Recognition Using 2D-ConvNet
There is huge requirement of continuous intelligent monitoring system for human activity recognition in various domains like public places, automated teller machines or healthcare sector. Increasing demand of automatic ...
Computer-aided ear diagnosis system based on cnn-lstm hybrid learning framework for video otoscopy examination
(IEEE-Inst Electrical Electronics Engineers, 2021)
Ear disorders are among the most common diseases treated in primary care, with a high
percentage of non-relevant referrals. The conventional diagnostic procedure is done by a visual examination
of the ear canal and ...
An introduction to deep learning on biological sequence data: Examples and solutions
(Oxford University Press, 2017-11)
Motivation: Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater ...