FTFNet: Multispectral Image Segmentation

1Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.

Abstract

Semantic segmentation is a machine learning task that is seeing increased utilization in multiple fields, from medical imagery to land demarcation and autonomous vehicles. A real-time autonomous system must be lightweight while maintaining reasonable accuracy. This research focuses on leveraging the fusion of long-wave infrared (LWIR) imagery with visual spectrum imagery to fill in the inherent performance gaps when using visual imagery alone. This approach culminated in the Fast Thermal Fusion Network (FTFNet), which shows marked improvement over the baseline architecture of the Multispectral Fusion Network (MFNet) while maintaining a low footprint.

Cite

CITATION STYLE

APA

Edwards, J., & El-Sharkawy, M. (2023). FTFNet: Multispectral Image Segmentation. Journal of Low Power Electronics and Applications, 13(3). https://doi.org/10.3390/jlpea13030042

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free