Solving multi-objective optimization problem of convolutional neural network using fast forward quantum optimization algorithm: Application in digital image classification

Convolutional neural network (CNN) has evolved as a new algorithm that has demonstrated its effectiveness in real-time issue solving over many other machine learning (ML) algorithms. However, many CNNs are created manually by considering randomly defined weights in the convolutional layer, pooling l...

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Veröffentlicht in:	Advances in engineering software (1992) Jg. 176; S. 103370
Hauptverfasser:	Singh, Pritpal, Muchahari, Monoj Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.03.2023
Schlagworte:	Convolutional neural networks (CNNs) Fast forward quantum optimization algorithm (FFQOA) Image classification Multi-objective Optimization Problem (MOOP) Convolutional neural networks (CNNs) Fast forward quantum optimization algorithm (FFQOA) Multi-objective Optimization Problem (MOOP) Image classification
ISSN:	0965-9978
Online-Zugang:	Volltext
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