Hyperspectral image classification has emerged as a transformative technology in Earth observation, providing unprecedented detail through hundreds of contiguous spectral bands. Neural network ...

Recent advances in neural network methodologies have revolutionised the analysis and classification of chromosome images, streamlining traditionally labour‐intensive processes in cytogenetics ...

Dr. James McCaffrey of Microsoft Research details the 'Hello World' of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset.

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification ...

Next, the demo creates and trains a neural network model using the MLPClassifier module ("multi-layer perceptron," an old term for a neural network) from the scikit library. [Click on image for larger ...

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

In other words, despite the staggering complexity of neural networks, classifying images -- one of the foundational tasks for AI systems -- requires only a small fraction of that complexity.

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.

The rise of large-scale artificial intelligence (AI) models, such as ChatGPT, DeepSeek, and autonomous vehicle systems, has ...