A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Recent advances in neural network methodologies have significantly reshaped the fields of electrical tomography and moisture analysis. By integrating artificial neural networks (ANNs) for both image ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...

ANKARA, TURKIYE - OCTOBER 8: An infographic titled "2024 Nobel Prize" created in Ankara, Turkiye on October 8, 2024. 2024 Nobel Prize in physics awarded to John J. Hopfield, Geoffrey E. Hinton for ...

Here’s an unusual concept: a computer-guided mechanical neural network (video, embedded below.) Why would one want a mechanical neural network? It’s essentially a tool to explore what it would take to ...

Synopsys has launched a new neural processing unit (NPU) intellectual property (IP) core and toolchain that delivers 3,500 TOPS to support the performance requirements of increasingly complex neural ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...