Researchers at FORTH have developed a new type of artificial neural network (ANN) that incorporates features of biological ...

One of the most agonizing experiences a cancer patient suffers is waiting without knowing: waiting for a diagnosis, waiting ...

Fiducial markers play a vital role in guiding robots by helping them navigate their environment and recognize objects. These ...

Neural AI (often referred to as neural network technology) applies pattern recognition on large datasets based on the complex ...

Scientists have developed a new kind of laser-based artificial neuron that mimics a biological nerve cell. This artificial ...

Access to AI intelligence should be equal to all. That means building collaborative systems of learning, like the Thames ...

Therefore, our training methods are more biologically plausible than artificial neural network training methods, such as backpropagation. (2) Our experimental results show that the ToM-SNN model can ...

Advancements could enhance perceptual capabilities in robotics. Artificially engineered biological processes, such as ...

Although SNNs are currently more efficient than artificial neural networks (ANNs), they are not as accurate as ANNs ... Consequently, our method can lower the possibility of vanishing spikes in BP ...

The neural network artificial intelligence models used in applications like medical image processing and speech recognition ...

In a research paper published by Optica, the researchers behind the system revealed it combines artificial intelligence (AI) ...

The VAE is like a funnel for training the software model to understand less common traffic situations, such as things on the ...