Himanshu Pathak emphasizes that next generation technologies will play a vital role in overcoming future agricultural ...

This review shows that machine learning enables early disease diagnosis, automates selective tea-bud harvesting, evaluates sensory quality using multi-sensor fusion, and predicts yields with higher ...

When NCSA’s partner, the Center for Digital Agriculture (CDA), formed more than five years ago, it put a heavy emphasis on artificial intelligence and machine learning (AI/ML) long before chat GPT ...

Predictability in agriculture is about as hard to find as a needle in a haystack. When you’re trying to prevent pest and disease pressures from devastating your yield, your approach to crop management ...

India’s agricultural sector is the backbone of its economy, employing nearly half the workforce and ensuring food security and rural livelihoods. Yet it faces mounting challenges—from climate change ...

International Conference on Climate Resilient Agriculture to be hosted by Banaras Hindu University ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.