Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data scientists should master both supervised ...

What if plants could speak when they were thirsty? Agriculture, in essence, is a dialog among crops, soil and climate. Yet drought, the most insidious stressor, remains largely silent until its damage ...

This study published in Robot Learning has been focused on water analysis using the combination of decision making and machine learning for a recently developed robotic system. The unique procedure ...

In the Age of AI, many health care providers dream of a digital assistant, unencumbered by fatigue, workload, burnout or ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Engineered nanozymes and explainable machine learning enable sensitive bacterial detection across complex conditions. The system uses three distinct signals and delivers transparent, verifiable ...

The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most ...

Security researchers have devised a technique to alter deep neural network outputs at the inference stage by changing model ...

Over the past decades, computer scientists have developed many computational tools that can analyze and interpret images.

Over the past decades, computer scientists have developed increasingly sophisticated sensors and machine learning algorithms ...