CLASSIFICATION OF PLANT LEAVES AND FLOWERS USING IMAGE PROCESSING AND DEEP NEURAL NETWORKS
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Abstract
Plants have shown an important role for our life and industry. In nature, there exists a large number of species of plants. The recognition and classification of plants is a challenging task. The understanding of plants allows us to develop various useful applications in our life. The paper presents a classification method of plant leaves and flowers using the image processing and deep neural networks (e.g., Alexnet, VGG, Resnet-50). The proposed method has been applied for leaves and flowers images that are collected and normalized from multiple sources. We have evaluated the proposed method on two public datasets: plant leaves and flowers. The large dataset is collected and prepared from various sources. The classification accuracies of 94% and 95% are obtained for the plant leaves and flowers, respectively. The obtained results have shown the effectiveness of our proposed method.
Keywords: Plant classification, Machine learning, Feature extraction, Deep neural networks
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