WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...
Learn With Jay on MSN

How Stride in CNNs Impacts Model Performance?

In this video, we will understand what is Stride in Convolutional Neural Network. While performing Convolution operation on an image, we move our filter by 1 pixel. It is called having the stride = 1.

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...
Physics World

Hybrid deep-learning model eases brachytherapy planning

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...
Edhat

AI Helps Explain How Covert Attention Works And Uncovers New Neuron Types

Shifting focus on a visual scene without moving our eyes — think driving, or reading a room for the reaction to your joke — ...

Designing Reactive AI With Spiking Neural Nets

Wolfram-like attention framing meets spiking networks: event-triggered, energy-thrifty AI that “wakes” to stimuli.
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.