CNN Approach for Identification of Medicinal Plants

Botanists and the public could identify plant species more quickly with the aid of an automated plant species identification system. Due to their critical role in maintaining human health, medicinal plants have long been researched and taken into consideration. Effective weed control is also necessary for modern farming since failure to control the weeds results in significant yield losses. However, it takes a lot of time and effort to identify medicinal plants, and a qualified expert is needed. Therefore, a vision-based approach can aid both scientists and regular people in properly and rapidly identifying herb plants. Deep learning is effective in extracting features because it excels at giving more detailed information about images. In this study, a brand-new CNN-based approach was suggested. A CNN block for feature extraction and a classifier block for categorizing the extracted features make up the proposed deep learning (DL) model. As a result, the suggested method can successfully replace conventional techniques and identify medicinal plants in real-time.