INT8 provides better performance with comparable precision than floating point for AI inference. But when INT8 is unable to meet the desired performance with limited resources, INT4 optimization is ...

Recent advances in light-weight deep learning models and network architecture search (NAS) algorithms are reviewed, starting with simplified layers and efficient convolution and including new ...

Jun Shu, Mingzhou Deng, Juncheng He, Optimization of Ship-borne Anti-collision Sounding System Based on Internet of Things and Full Convolution Neural Network, Journal of Coastal Research, SPECIAL ...

Researchers review AI-powered inverse lithography, showing how deep learning boosts chip patterning precision and efficiency ...

Simplex optimization is one of the simplest algorithms available to train a neural network. Understanding how simplex optimization works, and how it compares to the more commonly used back-propagation ...

Evolutionary optimization (EO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, EO can be used to train a neural network. EO is ...

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 ...