The main objective of this to classify the cereals, pulses and oil seeds using transfer learning of Convolution Neural Network (CNN) of deep learning.
Cereal grains vitally important in meeting the nutrient needs of the human population. Cereals are an upscale source of vitamins, minerals, carbohydrates, fats, oils, and protein. Legumes are an important source of protein, dietary fiber, carbohydrates and dietary minerals. Oilseeds are wont to make vegetable oils and biodiesel. Grain quality can have different aims to different people depending upon the sort of grain or seed and its intended use. Our objective is to develop a system to analyse the cereals, oilseeds and pulses. Hence, we develop a technique which is used to classify these cereals, oil seeds and the pulses using the deep learning technique which is a CNN based transfer learning method called Dense Net. Once after the classification, we apply the image processing technique on the classified output.
Keywords: Deep learning, image processing, CNN, Transfer learning, cereals, oil seeds, pulses
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

H/W Specifications:
β’ Processor : I3/Intel Processor
β’ RAM : 8GB (min)
β’ Hard Disk : 128 GB
S/W Specifications:
β’ Operating System : Windows 10
β’ Server-side Script : Python 3.6
β’ IDE : PyCharm
β’ Libraries Used : Numpy, IO, OS, Flask, keras.