Now showing items 1-6 of 6
Case Study: Deep Convolutional Networks in Healthcare
(Springer Verlag, 2020)
Technological improvements lead big data producing, processing and storing systems. These systems must contain extraordinary capabilities to overcome complexity of the big data. Therefore, the methodologies utilized for ...
Application of Deep Neural Networks for Disease Diagnosis Through Medical Data Sets
(Springer Science and Business Media Deutschland GmbH, 2019)
In this chapter, a novel classification methodology for medical disease diagnosis is proposed. The proposed classification operator comprises a stacked autoencoder network cascaded with a softmax layer. The classifier is ...
A deep learning architecture for identification of breast cancer on mammography by learning various representations of cancerous mass
Deep Learning (DL) is a high capable machine learning algorithm with the detailed analysis abilities on images. Although DL models achieve very high classification performances, the applications are trending on using and ...
The Effect of Auscultation Areas on Nonlinear Classifiers in Computerized Analysis of Chronic Obstructive Pulmonary Disease
Today, with the rapid development of technology, various methods are being developed for computer assisted diagnostic systems. Computer assisted diagnostic systems allow an objective assessment and help physicians to ...
Nonlinear and Chaotic Time Series Analysis
(World Scientific Publishing Co., 2022)
This study introduces the techniques used in the analysis of nonlinear and deterministic time series. Since chaotic time series are nonlinear and deterministic, the techniques introduced here can be successfully applied ...
A survey on p-adic integrals
(Springer International Publishing, 2019)
The p-adic numbers are a counterintuitive arithmetic system and were firstly introduced circa end of the nineteenth century. In conjunction with the introduction of these numbers, many mathematicians and physicists started ...