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Medicinal plants are widely used in non-industrialized societies, mainly because they are readily available and cheaper than modern medicines. These herbs that have medicinal quality provide rational means for the treatment of many internal diseases, which are otherwise considered difficult to cure. This is the reason why medicinal plant related analysis is growing in popularity across the researchers. The prime difficult in this medicinal plant treatment is the identification of those plants. Without any expert, the identification is difficult. The image processing methodologies are the dominant method for solving this kind of problem. This paper is addressing a solution for the medicinal plant identification using deep learning networks. The deep learning algorithm is a class of machine learning algorithms that uses multiple layers to progressively extract higher level features from the raw input. From this approach, different kind of plants can be easily identified and the state-of-art of this approach is the speed of operation and precision in identification. The proposed approach is implemented on both dataset as well as experimental images
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