vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff71732e0000006c20000001000e00
Medicinal Plants are the main resource base of Indian autochthonic health care traditions called Ayurveda. The general use of ayurvedic preparation is also common without ill effects. As advancement in Image Processing, Image Analytics techniques transpiring, researchers in the machine learning and computer vision fields are striving to achieve accurate automatic plant identification and classification. This paper focuses on the Automatic Indian Ayurvedic plant identification based on muti organ images analytics. A lot of research work has been carried out for the identification of plants by their leaves, this research carries out multi organ-based identification of Indian Medicinal plants. This paper proposes IMPINet which is a network developed for Indian Medicinal Plant Identification. IMPINet is a non-sequential deep network having multiple convolutions at the same level. A novel approach for multiorgan based plant identification is also proposed where final accuracy is calculated by score-based fusion. Comparison of IMPINet has been carried out with the state of art networks and performance of IMPINet is evaluated on benchmark dataset Flavia