Power Plant Detection for Energy Estimation using GIS with Remote Sensing, CNN & Vision Transformers

Autor:	Austin-Gabriel, Blessing, Monsalve, Cristian Noriega, Varde, Aparna S.
Rok vydání:	2024
Předmět:	Computer Science - Machine Learning Computer Science - Computer Vision and Pattern Recognition I.2.m J.2
Zdroj:	IEEE Sensors 2024 Conference
Druh dokumentu:	Working Paper
Popis:	In this research, we propose a hybrid model for power plant detection to assist energy estimation applications, by pipelining GIS (Geographical Information Systems) having Remote Sensing capabilities with CNN (Convolutional Neural Networks) and ViT (Vision Transformers). Our proposed approach enables real-time analysis with multiple data types on a common map via the GIS, entails feature-extraction abilities due to the CNN, and captures long-range dependencies through the ViT. This hybrid approach is found to enhance classification, thus helping in the monitoring and operational management of power plants; hence assisting energy estimation and sustainable energy planning in the future. It exemplifies adequate deployment of machine learning methods in conjunction with domain-specific approaches to enhance performance.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.04986 Zobrazit plný text záznamu View this record from Arxiv