Leveraging LSTM and ensemble classifiers for enhanced food waste classification

Leveraging LSTM and ensemble classifiers for enhanced food waste classification

Abstract A long short-term memory (LSTM)-enhanced feature extraction technique was combined with ensemble classifiers (gradient boosting, logistic regression, random forest, and support vector machine (SVM)) to improve waste classification outcomes. The proposed feature extraction approach detects t...

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Bibliographic Details
Main Author: Khalaf Alsalem
Format: Article
Language:English
Published: Springer 2025-05-01
Series:Discover Sustainability
Subjects:
Food waste classification
Machine learning
LSTM
Ensemble classifiers
Online Access:https://doi.org/10.1007/s43621-025-01330-6
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https://doi.org/10.1007/s43621-025-01330-6

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