Neural networks are algorithmic systems created based on the principle of the human nervous system. They consist of many ...
A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...
Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...
In the ever-evolving world of artificial intelligence, deep neural networks (DNNs) have revolutionized data processing, offering unparalleled accuracy across various ...
Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...
A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of ...
The LHCb collaboration developed an inclusive deep-learning flavour tagger for neutral B-mesons, improving tagging power by ...
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