Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various ...

The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my ...

One of the most striking claims in the review is that AI-based classification models can meet or exceed the performance of expert radiologists in diagnosing ILDs, particularly in identifying patterns ...

Some representations make it easier to learn tasks (e.g., face recognition or spoken word recognition) from examples. One of the promises of deep learning is replacing handcrafted features with ...

From predictive analytics to autonomous control, AI is making renewable energy systems smarter, faster, and more efficient.

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected ...

These platforms, equipped with deep learning algorithms, have opened a world of possibilities, enabling smart devices, autonomous systems, and intelligent applications. The deployment of deep learning ...

For example, if you want to automatically detect atrial fibrillation, a common type of irregular heart rhythm, you need to tell the machine-learning algorithm what atrial fibrillation looks like.