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

Quantum machine learning can play an essential role in smart manufacturing applications.
This paper aimed to understand the state of the art of quantum computing in machine …

Quantum computing, a field utilizing the principles of quantum mechanics, promises great
advancements across various industries. This survey paper is focused on the burgeoning …

In this work, we propose a quantum neural network named quantum perceptron over a field
(QPF). Quantum computers are not yet a reality and the models and algorithms proposed in …

This paper makes an exhaustive survey of various applications of Quantum inspired
computational intelligence (QCI) techniques proposed till date. Definition, categorization and …

A method is proposed for solving the two key problems facing quantum neural networks:
introduction of nonlinearity in the neuron operation and efficient use of quantum …

A new machine learning approach for price modeling is proposed. The use of neural
networks as an advanced signal processing tool may be successfully used to model and …

Autonomous poststroke rehabilitation systems which can be deployed outside hospital with
no or reduced supervision have attracted increasing amount of research attentions due to …

This paper aims at solving time series prediction problems by means of a hybrid quantum-
classical recurrent neural network. We propose a novel architecture based on stacked Long …

A supervised learning algorithm for quantum neural networks (QNN) based on a novel
quantum neuron node implemented as a very simple quantum circuit is proposed and …