Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Saragoor Madanayaka, Devendra Kumar
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Adaptive transformer architecture for scalable earth observation via hyperspectral imaging Saragoor Madanayaka, Devendra Kumar; Muthukrishnan, Devanathan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp824-830

Abstract

Hyperspectral Image (HSI) classification is one of the critical processes involved in remote sensing application that plays a crucial role towards earth observation. Owing to complex spatial-spectral relationship and high dimensionality, it is quite a challenging task to subject HSI content to conventional data analytics or existing methods. Hence, the proposed study introduces a novel computational model known as Adaptive Spectra-Spatial Transformer (ASST) to address these ongoing challenges and shortcoming of existing Artificial Intelligence (AI) based modelling. The proposed model contributes towards a novel transformer-based architecture where a distinct spectral-spatial attention method has been used with transformer encoder. This novel combination facilitates highly adaptive and contextually enriched feature extraction. Tested on universally standard HSI dataset of Pavia University, the proposed ASST model has been benchmarked with notice 97.26% of overall accuracy and faster processing duration computed via training and response time in contrast to frequently adopted ML and DL models. The accomplished study outcomes truly exhibited highly improved feature representation as well as robust performance against class imbalance problems towards scalable data analysis of HSI contents for earth observation.
Co-Authors Muthukrishnan, Devanathan