QNNs achieved 95 percent accuracy, while QSVMs reached 94 percent, both surpassing classical machine learning methods, which ...

With this bat-inspired technology, the potential to locate more survivors the next time an earthquake or wildfire strikes ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

Department of Chemistry and Biochemistry, University of Wisconsin─Eau Claire, Eau Claire, Wisconsin 54702, United States ...

Whether it's powering your phone’s autocorrect or helping someone create a new recipe with a few words, artificial intelligence (AI) is everywhere right now. But if you're still nodding along when ...

Learn about the Network in Network architecture and its impact on improving performance in deep neural networks using PyTorch. At least 11 people injured in stabbing at Michigan Walmart ‘Dismiss Fox ...

Advances in deep learning methods have demonstrated remarkable progress in wheelset fault diagnosis. However, current deep neural networks suffer from design flaws, including low accuracy, high ...

Abstract: The goal of this study is to detect online gaming addiction in young individuals using two types of neural networks: a novel recurrent neural network and a convolutional neural network. The ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...