A hyperspectral unmixing model using convolutional vision transformer

Bhakthan, Sreejam Muraleedhara; Loganathan, Agilandeeswari

doi:10.1007/s12145-024-01273-y

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.

A hyperspectral unmixing model using convolutional vision transformer

Cited by 4 publications

References 36 publications

Hyperspectral Image Super-Resolution Based on Dual-Domain Gated Attention Network

Hyperspectral Image Super-Resolution Based on Dual-Domain Gated Attention Network

Enhanced hyperspectral image analysis via 2D-3D CNN fusion and hybrid moth-flame optimization for optimal band selection in remote sensing

DeepSecure watermarking: Hybrid Attention on Attention Net and Deep Belief Net based robust video authentication using Quaternion Curvelet Transform domain

Contact Info

Product

Resources

About