Evaluating the impact of hyperparameters on the performance of 1D CNN model for nutritional profiling of underutilized crops using NIRS data

Evaluating the impact of hyperparameters on the performance of 1D CNN model for nutritional profiling of underutilized crops using NIRS data

The application of 1D Convolutional Neural Networks (CNNs) for nutritional profiling using Near-Infrared Spectroscopy (NIRS) data has increased significantly in recent times. The accuracy of 1D CNNs depends on hyperparameters, yet a thorough investigation into their impact on model performance is la...

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Bibliographic Details
Main Authors: Simardeep Kaur, Naseeb Singh, Amit Kumar, Philanim W S, Veerendra Kumar Verma, Amit Kumar Patil, Rakesh Bhardwaj, Amritbir Riar
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Smart Agricultural Technology
Subjects:
Deep learning
Neural networks
Nutritional profiling
NIRS
Orphan crops
Chemometrics
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525002588
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