GENERALIZATION PERFORMANCE OF QUANTUM METRIC LEARNING CLASSIFIERS

Generalization Performance of Quantum Metric Learning Classifiers

Quantum computing holds great promise for a number of fields including biology and medicine.A major application in which quantum computers could yield advantage is machine learning, especially Kitchen Knives kernel-based approaches.A recent method termed quantum metric learning, in which a quantum embedding which maximally separates data into class

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Improved stereo matching algorithm based on multi-scale fusion

Aiming at the low matching accuracy of local stereo matching algorithm in weak texture or discontinuous disparity areas, a stereo matching algorithm combining multi-scale fusion of convolutional neural network (CNN) and feature pyramid structure (FPN) is proposed.The feature pyramid is applied on the basis of the convolutional neural network to rea

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Approach Based Lightweight Custom Convolutional Neural Network and Fine-Tuned MobileNet-V2 for ECG Arrhythmia Signals Classification

Arrhythmia detection in electrocardiogram (ECG) signals is a vital aspect of cardiovascular health monitoring.Current automated methods for arrhythmia classification often struggle to attain satisfactory performance in the detection of various heart conditions, particularly when dealing with imbalanced datasets.This study introduces a novel deep le

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