Fusion of 3D feature extraction techniques to enhance classification of spinocerebellar ataxia type 12

Agrawal, Snigdha; Agrawal, Ramesh Kumar; Kumaran, S. Senthil; Srivastava, Achal Kumar; Narang, Manpreet Kaur

doi:10.1007/s41870-023-01579-y

Int. j. inf. tecnol.

2023

DOI: 10.1007/s41870-023-01579-y

|View full text |Cite

Fusion of 3D feature extraction techniques to enhance classification of spinocerebellar ataxia type 12

Snigdha Agrawal,

Ramesh Kumar Agrawal,

S. Senthil Kumaran

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A novel and proposed triad machine learning-based framework for the prognosis of Huntington’s disease

Deepak,

Ojha,

Acharjya

et al. 2024

Int. j. inf. tecnol.

View full text Add to dashboard Cite

A novel and proposed triad machine learning-based framework for the prognosis of Huntington’s disease

Deepak,

Ojha,

Acharjya

et al. 2024

Int. j. inf. tecnol.

View full text Add to dashboard Cite

OntoMG: a unique and ontological-based intelligent framework for early identification of myasthenia gravis (MG)

Mahajan,

Agarwal,

Vekariya

et al. 2024

Int. j. inf. tecnol.

View full text Add to dashboard Cite

Reducing noise using neighbourhood pixel analysis and interpretable custom kernel in CNN model for CP handwritten digit recognition

Muthureka,

Srinivasulu Reddy,

Janet

2024

Int. j. inf. tecnol.

View full text Add to dashboard Cite

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

customersupport@researchsolutions.com

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

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

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.

Fusion of 3D feature extraction techniques to enhance classification of spinocerebellar ataxia type 12

Cited by 3 publications

References 64 publications

A novel and proposed triad machine learning-based framework for the prognosis of Huntington’s disease

A novel and proposed triad machine learning-based framework for the prognosis of Huntington’s disease

OntoMG: a unique and ontological-based intelligent framework for early identification of myasthenia gravis (MG)

Reducing noise using neighbourhood pixel analysis and interpretable custom kernel in CNN model for CP handwritten digit recognition

Contact Info

Product

Resources

About