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Deep Learning for Wheat Variety Classification by Anubhav Jay is a document available to read on EtoBox.

The document discusses wheat crop production and quality assessment processes including seed testing and purity tests. It then proposes a deep learning approach using convolutional neural networks to classify wheat grain images into four varieties with a dataset of over 31,000 images. The best models for varietal level classification were DenseNet201, Inception V3, and MobileNet which achieved over 95% test accuracy.

Author
Anubhav Jay
Language
EN