The project titled "Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks" aims to develop a robust and accurate machine learning model for the automatic ...

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, according ...

Abstract: In recent years, real-valued neural networks have made significant progress in computer vision tasks such as image classification, object detection, and semantic segmentation. However, ...

Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...

Weed management presents a major challenge to vegetable growth. Accurate identification of weeds is essential for automated weeding. However, the wide variety of weed types and their complex ...

Addressing the issues with insufficient multi-scale feature perception and incomplete understanding of global information in traditional convolutional neural networks for image classification of wheat ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...