Computational complexities in modern power systems are reportedly increasing daily, and it
is anticipated that traditional computers might be inadequate to provide the computation …

Quantum neural network is a useful tool which has seen more development over the years
mainly after twentieth century. Like artificial neural network (ANN), a novel, useful and …

We introduce a general method for building neural networks on quantum computers. The
quantum neural network is a variational quantum circuit built in the continuous-variable (CV) …

Traffic congestion prediction (TCP) plays a vital role in intelligent transportation systems due
to its importance of traffic management. Methods for TCP have emerged greatly with the …

In this paper, we propose a novel Hadamard Transform (HT)-based neural network layer for
hybrid quantum-classical computing. It implements the regular convolutional layers in the …

Machine Learning (ML) aims at designing models that learn from previous experience,
without being explicitly formulated. Applications of machine learning are inexhaustible …

The past few years have witnessed a huge increase in the application of facial recognition,
detection, and analysis technology. However, face recognition systems remain the most …

Quantum mechanism, which has received widespread attention, is in continuous evolution
rapidly. The powerful computing power and high parallel ability of quantum mechanism …

Perceptrons are the basic computational unit of artificial neural networks, as they model the
activation mechanism of an output neuron due to incoming signals from its neighbours. As …

Lithology interpretation is important for understanding subsurface properties. Yet, the
common manual well log interpretation is usually with low efficiency and bad consistency …