These efforts are promising but limited. AI minds don't necessarily map to human concepts. Some believe that we need to ...

A team of scientists in the United States has combined both spatial and temporal attention mechanisms to develop a new approach for PV inverter fault detection. Training the new method on a dataset ...

Here we proposed a hybrid neural network (Hybrid-NN) as a novel scheme to improve the detection performance in terms of validation accuracy and required training data amount. The idea is to insert ...

Researchers in the field of Neuromorphic Engineering are looking at ways to reduce the chip space required to mimic the huge processing capacity of the human brain and to simplify algorithms to train ...

[1] F. Scarselli, M. Gori, A.C. Tsoi, M. Hagenbuchner, and G. Monfardini. The graph neural network model. IEEE Transactions on Neural Networks, 20(1):61 80, 2009.

Several years ago, a group of researchers from OpenAI, one of the leading artificial intelligence research labs in the world, noticed a surprising phenomenon when they were training a neural network.

Abstract: The detection of potholes in asphalt has been a concern in the field of deep learning to identify patterns with the best possible accuracy. In the smart city concept, autonomous cars are ...

Your grade school teacher probably didn’t show you how to add 20-digit numbers. But if you know how to add smaller numbers, all you need is paper and pencil and a bit of patience. Start with the ones ...

Neural networks remain a black box whose inner workings engineers and scientists struggle to understand. Now, a team led by data and computer scientists at the University of California San Diego has ...

Real data can be hard to get, so researchers are turning to synthetic data to train their artificial intelligence systems. On a sunny day in late 1987, a Chevy van drove down a curvy wooded path on ...