Article
Plant Leaf Classification Using a Compact Deep Learning Model Use of VGG-16
Systematic plant-based categorization has never been difficult. Targeted crop safety is dependent on automated technologies that detect and classify plants. Classical machine learning approaches have been used to categorize leaves using handcrafted features from the shape of plant leaves, which have yielded promising results. However, we concentrate on classifying plant leaves using non-handcrafted traits. To accomplish this, we employ the use of deep learning for extraction of features and categorization. Deep Convolution Neural Networks have recently demonstrated impressive achievements in picture classification and object detection challenges. This paper proposes using the built-in, compact VGG-16 model to detect and classify ten plant species from the Plant dataset. The proposed models are utilized to classify ten other classes.When contrasted with other pre-trained models, VGG -16 fared better in categorizing leaf images. Computerized plant species categorization could be beneficial to food engineers, agricultural professionals, researchers, and the general public.
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