WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

The threat to software-as-we-know-it comes from digital data: the foundational, eight-decades-long trend driving the ...

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 ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

The case was the first trial of more than 3,000 similar lawsuits against Uber that have been consolidated in U.S. federal ...

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

Snowflake’s Artin Avanes explains why governance should be built into a small business’s data foundation to achieve ...

The optimized detection model is integrated into both a mobile application and a dedicated edge device, demonstrating that real-time waste detection can operate reliably without cloud connectivity.

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

A flexible electronic skin stacks carbon nanotube layers to sense touch position and pressure simultaneously, performing classification through its physical structure rather than external processors.