Alzheimer's Disease Detection Using Sparse Autoencoder, Scale Conjugate Gradient and Softmax Output Layer With Fine Tuning

International Journal of Machine Learning and Computing - Singapore
doi 10.18178/ijmlc.2017.7.1.612
Full Text
Abstract

Available in full text

Date
Authors
Publisher

EJournal Publishing

Related search

A Sparse Autoencoder and Softmax Regression Based Diagnosis Method for the Attachment on the Blades of Marine Current Turbine

2019English

Hand Detection Using Cascade of Softmax Classifiers

Advances in Multimedia
Computer Science
2018English

Multi-Scale Sparse Coding With Anomaly Detection and Classification

2016English

Early Detection of Alzheimer's Disease Using PiB and FDG PET

Neurobiology of Disease
Neurology
2014English

A Parameteric Conjugate Gradient Methods for Large Scale Problem

2016English

Full Scale Bridge Damage Detection Using Sparse Sensor Networks, Principal Component Analysis, and Novelty Detection

Proceedings
2019English

Identification of Alzheimer's Disease and Mild Cognitive Impairment Using Multimodal Sparse Hierarchical Extreme Learning Machine

Human Brain Mapping
Nuclear MedicineRadiologyUltrasound TechnologyAnatomyRadiologicalNeurologyImaging
2018English

Detection of Cataract and Conjunctivitis Disease Using Histogram of Oriented Gradient

International Journal of Engineering and Technology
Transfer ProcessesFluid FlowMechanical EngineeringAerospace Engineering
2017English

A New Accelerated Conjugate Gradient Method for Large-Scale Unconstrained Optimization

Journal of Inequalities and Applications
CombinatoricsApplied MathematicsAnalysisDiscrete Mathematics
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy