The Lp-Convolution technique enhances AI image recognition, mimicking brain processes to improve accuracy and efficiency while reducing computational demands.

Ceva, the leading licensor of silicon and software IP that enables Smart Edge devices to connect, sense and infer data more reliably and efficiently, announced that Nextchip has licensed the NeuPro-M ...

A team of researchers from the Institute for Basic Science, Yonsei University, and the Max Planck Institute have developed a ...

Researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have developed a neural network model based on self-attention mechanisms to rapidly predict radiation ...

Neural networks are one typical structure on which artificial intelligence can be based. The term "neural" describes their ...

Concerns about AI's energy use have a lot of people looking into ways to cut down on its power requirements. Many of these ...

A new editorial was published in Oncotarget, Volume 16, on April 4, 2025, titled “Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.” ...

This research introduces a federated hybrid TSC method that combines image-based time series representation techniques with Convolutional Neural Networks (CNNs) in a decentralized framework.

This course studies a selection of advanced techniques in Natural Language Processing (NLP), with particular emphasis ... a type of machine learning techniques using artificial neural networks.

Quantum Convolutional Neural Networks (QCNNs) show promise in processing large-scale image data with improved efficiency and accuracy. However, most of QCNN researches focus on grayscale image ...