Scanning tunneling state recognition with multi-class neural network ensembles

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Class-switching neural network ensembles

This article investigates the properties of class-switching ensembles composed of neural networks and compares them to class-switching ensembles of decision trees and to standard ensemble learning methods, such as bagging and boosting. In a class-switching ensemble, each learner is constructed using a modified version of the training data. This modification consists in switching the class label...

متن کامل

Neural Network Ensembles

We propose several means for improving the performance and training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining residual “generalization” error can be reduced by invoking ensembles of similar networks. Zndex Terms-Crossvalidation, fault tolerant computing, neural networks, N-versio...

متن کامل

Multi-class SVM Classifier With Neural Network For Handwritten Character Recognition

The paper describes the process of character recognition using the Multi Class SVM classifier combined with a neural Network approach. The character recognition techniques or the OCRs are either a printed document recognition or the handwritten character recognition. SVM (Support Vector Machine) classifiers often have superior recognition rates in comparison to other classification methods. In ...

متن کامل

Predicting Software Reliability with Neural Network Ensembles

Software reliability is an important factor for quantitatively characterizing software quality and estimating the duration of software testing period. Traditional parametric software reliability growth models (SRGMs) such as nonhomogeneous Poisson process (NHPP) models have been successfully utilized in practical software reliability engineering. However, no single such parametric model can obt...

متن کامل

Speaker-independent connected letter recognition with a multi-state time delay neural network

We present a Multi-State Time Del ay Neural Network (MS-TDNN) for speaker-i ndependent, connected l etter recogni ti on. Our MS-TDNNachi eves 98. 5/92.0% word accuracy on speaker dependent/i ndependent Engl i sh l etter tasks[7, 8]. In thi s paper we wi l l summari ze several techni ques to improve (a) conti nuous recogni ti on performance, such as sentence l evel trai ni ng, and (b) phoneti c ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Review of Scientific Instruments

سال: 2019

ISSN: 0034-6748,1089-7623

DOI: 10.1063/1.5099590