Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Recent advancements in neural network methodologies have revolutionised hydrological forecasting, enabling more accurate, robust and computationally efficient predictions of water resource dynamics.

Recent advancements in neural network optimisation have significantly improved the efficiency and reliability of these models in handling complex tasks ranging from pattern recognition to multi-class ...

Real-time object detection on mobile platforms is a crucial but challenging computer vision task. However, it is widely recognized that although the lightweight object detectors have a high detection ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion. They trained a convolutional neural network (CNN) with ...

For the past decade, AI researcher Chris Olah has been obsessed with artificial neural networks. One question in particular engaged him, and has been the center of his work, first at Google Brain, ...

Mingi Kang ’26 received a Fall Research Award from Bowdoin this semester to support his project exploring how two distinct ...