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Artificial neural networks

Fine-Grained Hierarchical Singular Value Decomposition for Convolutional Neural Networks Compression and Acceleration

Research into convolutional neural networks (CNNs) has led to significant advancements in the field of computer vision, especially in industrial-embedded scenarios. Despite the increasing availability of modern artificial intelligence chips, making CNNs more lightweight remains a crucial challenge. A new study proposes a novel matrix decomposition method, termed hierarchical singular

Artificial neural networks

AI Accelerates Materials Design and Development in Nanotechnology

Nanotechnology researchers at Johns Hopkins University have discovered that artificial intelligence (AI) models can significantly accelerate materials design and development. By employing convolutional neural networks (CNN) models, the researchers were able to characterize DNA origami nanostructures, which have numerous applications in biomedicine. The study, published in the Journal of Chemical