Deep Learning Model for Identifying Snakes by using Snakes’ Bite Marks

Abstract

Identifying snakes by using their bite marks may help the doctors to diagnose the victim with proper anti venoms for saving patients. It is very important step for doctors to help the patients who suffered by snakes bites. Hence here a study was done on processing images to classify them as different family of snakes using CNN (Convolution Neural Network) model in Deep Learning techniques. The CNN model needs different snakes and their bite marks images to classify them as venomous and non-venomous snakes and by processing venomous snakes bite marks images it can able to find the venomous snakes family. To give accurate results the proposed Deep learning model has to be trained periodically with all possible different images of same snake’s family and different snakes’ families. The performance of the CNN model is on its knowledge and finding patterns on the input images to find the family of the snakes. If the input images are huge in numbers and size then the system may take time to give results. That has to be considered to give results in less duration execution time.