• Sumit Shinde
• C.G.Patil
• Ashwini Kalgunde
• S.S.Bhosale
• Nikhil Ganvir,S. N. Kamble

These days, a large portion of the people groups don't know about their country and metropolitan restorative plants and their employments. Assuming we need to discover the plant subtleties for their restorative qualities, we must be presented to it beforehand. Nonetheless, certain individuals will see it to be a drawn-out measure since they don't know about these plants previously. Also, at certain occasions, we need to rely upon others for the distinguishing proof of restorative plants. (i.e.) an expert in or student of the scientific study of plants. So to stay away from this load of sorts of circumstances and with the accessibility of current figuring gadgets and innovation we will create a module (Profound Neural Organizations) for the distinguishing proof of restorative plants. To prepare the model we utilized around 1,834 pictures having a place with four various classes. We might get showed up with great response when testing with pictures taken from rural and urban areas. In this system, the herbal plant leaf recognition system is implemented using CNN, Vgg16 and Vgg19 algorithms. The training of the proposed system is performed using google colab cloud platform. The proposed system gives the promising results.

Herbal Plants, Classification, Image recognition, Convolutional Neural Network.

"Deep Learning Approach for Herbal Plant Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.347-353, August-2022, Available :http://www.jetir.org/papers/JETIRFP06061.pdf

"Deep Learning Approach for Herbal Plant Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. pp347-353, August-2022, Available at : http://www.jetir.org/papers/JETIRFP06061.pdf