There is a long history of artificial ... neural network, including its settings, and to perform proper training, validation and testing. Evolutionary algorithms may, however, help designing networks ...

For some time, organic fibers were added to gypsum, but artificial fibers were ... values are approximated by trained neural network efficiently. However, RSM model was slightly accurate. Comparison ...

Finally, we proceed to the pivotal stages of model training and testing, employing the Densenet Convolution Neural Network (DCNN) architecture coupled ... using ML techniques based on Artificial ...

They highlight that current methods, including top-down approaches that focus on model constraints and bottom-up approaches that detail the operational sequences, fail to provide a holistic view of ...

Here, we consider the data from this competition as an example to illustrate the utility of fully connected cascade (FCC) artificial neural network (ANN) architecture for performing classification. We ...

Florence Nightingale’s innovative “rose diagram” of preventable deaths ... a supervised classification algorithm or an artificial neural network) and human-curated methods can be applied ...

WASHINGTON, April 24(Reuters) - The U.S. Supreme Court on Monday declined to hear a challenge by computer scientist Stephen Thaler to the U.S. Patent and Trademark Office's refusal to issue ...

However, it wasn’t until recently that the necessary training data, neural-network frameworks, and the requisite processing power came together to help launch an artificial-intelligence (AI ...

In this paper, we propose a novel augmented artificial intelligence approach using an artificial neural network (ANN) with particle swarm optimization ... proposed model architecture, classification ...

it uses knowledge distillation to project a pre-trained neural network onto the set of TNNs with low-rank tensor structures, and (2) it exploits these low-rank tensor structures, which naturally ...