MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, have developed a quantum algorithm technology for deep convolutional neural network (CNN) exchange ...

Scientists at Washington University in St. Louis have made a groundbreaking leap in neuroscience by developing a method for ...

Abstract: Deep learning has been successfully applied to solve the synthetic aperture radar (SAR) imaging problem, which shows superior imaging performance to compressive sensing (CS)-based methods ...

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network… ...

Researchers have developed a transfer learning-enhanced physics-informed neural network (TLE-PINN) for predicting melt pool morphology in selective laser melting (SLM). This novel approach combines ...

These optimization methods focus on actual implementation challenges ... z is the input to the ONN layer and the complex conjugate is taken for complex-valued neural networks. Models with selected ...

Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog ...

Graph Neural Networks GNNs have become a powerful tool for analyzing graph-structured data, with applications ranging from social networks and recommendation systems to bioinformatics and drug ...

U.S. telecom giants AT&T and Verizon say they have secured their networks after being targeted by the China-linked Salt Typhoon cyberespionage group. In a statement given to TechCrunch on Monday ...

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network… ...