Abstract: Large-scale data clustering is an essential key for big data problem. However, no current existing approach is “optimal” for big data due to high complexity, which remains it a great ...

Forest fires are highly destructive. They not only damage forest ecosystems, but also threaten the lives and property of surrounding residents, causing incalculable losses. Effective forest ...

The growing demand for energy-efficient Wireless Sensor Networks (WSNs) in applications such as IoT, environmental monitoring, and smart cities has sparked exhaustive research into practical solutions ...

As geospatial datasets grow in scale, complexity, and dimensionality, traditional computing methods are increasingly strained in delivering real-time spatial insights. Quantum computing, a field once ...

Abstract: Clustering image pixels is an important image segmentation technique. While a large amount of clustering algorithms have been published and some of them generate impressive clustering ...

ChatGPT has gone viral since OpenAI released the text-based artificial intelligence tool last month. It's the latest development in the world of generative AI, which has attracted billions of dollars ...

BIRCH is an alternative to MinibatchKMeans and is designed for large datasets. The algorithm converts data into a tree structure, facilitating efficient clustering. Clustering is the process of ...

Rodents engage in active touch using their facial whiskers: they explore their environment by making rapid back-and-forth movements. The fast nature of whisker movements, during which whiskers often ...

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following explicit ...