• Harishankar P

Plants are the backbone of life on earth, as it provides us food and oxygen. Hence, a good understanding of plants is needed to help in identifying new or rare plant species. Such identification will in turn improve the drug industry, balance the ecosystem as well as the agricultural productivity and sustainability. With increasing population it has become inevitable but to increase agricultural productivity. But various diseases and conditions affecting the crops and lack of knowledge on crop management is affecting cultivation. A method to classify plants or crops and provide knowledge about cultivating the species and managing harmful conditions will be useful for increased production. Recognition of Plant from images is a challenging computer vision task. The various types of challenges are many parts of the plant, which need to be identified, are also diverse in nature with high intra class variations and small inter class variations. Object detection is one of the most important topics in digital image analysis. In object detection the system automatically locates an object from the given input image and then classify the object into one of the different available categories. Object detection has found its use in many systems like autonomous cars, video surveillance and many other applications. There are different object detection models available which are broadly classified into 2, region based and regression based. Now regression based models use CNN along with deep learning and are considered to be best suited for object detection. CNN(Convolution Neural Networks), an extension of ANN(Artificial Neural Networks, simulates the working of human neural network using a multilayer structure that incrementally extract features from the given input image from lower to higher layer until it comes across an ideal feature for pattern classification. For an object detection model to work we have two main requirements i.e. a dataset to train the model and then a good graphical processing unit(GPU).

agriculture, plant classification, convolutional neural networks, deep learning, computer vision.

"Disease and deficiency detection in plants using leaf classification and color segmentation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.357-362, May-2019, Available :http://www.jetir.org/papers/JETIR1905I53.pdf

"Disease and deficiency detection in plants using leaf classification and color segmentation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp357-362, May-2019, Available at : http://www.jetir.org/papers/JETIR1905I53.pdf