Abstract:
Deep Learning is an uprising technology in terms of image classification. It has
reached greater heights in forms of performance and accuracy with the advanced
ability to perform better in face of large data sets. The traditional approach for model
fitting, initiated with the arriving to decision on a model of data followed with a
parameter estimated with that data. Machine learning has altered this method
completely by using an algorithm to ensure the connection between inputs and
outputs instead of starting off with a data model. ML approach in pattern recognition
is focused on learning outcomes by perceiving the inputs and detecting critical
patterns in it.
FruitScape is a disease detection and fertilizer recommendation application built on
top of a deep learning module that comprises of the capability to identify different
stages the infection level and provide the specific recommendation based on the
predictions. It provides an ultimate solution adhering all the problems faced by the
farming community due to diseases and inability to identify them in a timely
manner. The expertise and experience required by a farmer to predict and decide on
a fertilizer to overcome the disease is replaced by fruitscape. This is an escape to the
fruit diseases.
