A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification

Fourati, Jihen; Othmani, Mohamed; Ltifi, Hela

doi:10.5220/0010773600003116

Proceedings of the 14th International Conference on Agents and Artificial Intelligence 2022

DOI: 10.5220/0010773600003116

|View full text |Cite

A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification

Jihen Fourati

Mohamed Othmani

Hela Ltifi

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

2023

Publication Types

Select...

Book4

Relationship

Self Cite0

Independent4

Authors

Journals

Cited by 4 publications

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A Hybrid Model based on Convolutional Neural Networks and Long Short-term Memory for Rest Tremor Classification

Cited by 4 publications

References 0 publications

Long Short-Term Memory Based Photoplethysmography Biometric Authentication

Long Short-Term Memory Based Photoplethysmography Biometric Authentication

An Improved Model for Semantic Segmentation of Brain Lesions Using CNN 3D

An Improved Multi-image Steganography Model Based on Deep Convolutional Neural Networks

Contact Info

Product

Resources

About