IEEE

Prediction of Land Use and Land Cover Using Google Earth Engine (GEE) and Machine Learning Algorithms: A Review

Abstract: Reliability is a critical requirement for classifiers that generate maps of land use and land cover (LULC), and these classifiers are highly sought after. Particularly, machine learning ...
IEEE

Cluster Head Selection Algorithm using Machine Learning

Abstract: Wireless Sensor Networks (WSNs) find extensive applications in environmental monitoring, healthcare, and smart cities. Energy efficiency, however, continues to be a significant challenge ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
GitHub

A minimal, secure Python interpreter written in Rust for use by AI.

Experimental - This project is still in development, and not ready for the prime time. A minimal, secure Python interpreter written in Rust for use by AI. Monty avoids the cost, latency, complexity ...