A Novel 1D-DenseNet-Like Architecture for Enhanced Raisin Grain Classification

This study introduces a novel sparse one-dimensional dense convolutional network-like (1D-DenseNet) architecture, optimized explicitly for raisin variety classification. By combining advanced deep learning techniques with a concise set of seven pre-extracted morphological features, our method signif...

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Bibliographic Details

Main Author:	Thi-Thu-Hong Phan
Format:	Artigo
Language:	Inglês
Published:	World Scientific Publishing 2026-05-01
Series:	Vietnam Journal of Computer Science
Subjects:	Raisin grain classification 1D-DenseNet morphological features hybrid model classification accuracy
Online Access:	https://www.worldscientific.com/doi/10.1142/S2196888825500101
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