Wildlife Detection System Using Deep Neural Networks

Wildlife Detection System Using Deep Neural Networks

Mrs. Anjana HS1, Bhoomika BR2, Chethan S Pateel3, HN Raksha4, M Phaneedra5
1 Assistant Professor, Dept of ISE, East West Institute Of Technology, Bengaluru

2,3,4,5 Student, Dept of ISE, East West Institute Of Technology, Bengaluru

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Abstract –
Animals moving out of the forest region and moving into the human environment is growing day by day. Animals entering the farming regions put close to the forest ruin crops or even assault on people therefore there is a need of system which detects the animal existence and gives caution about that in the position of security objective. The proposed project “Wildlife Detection using Deep Neural Networks” provides the users with type of animal and count to make the process of animal vehicle collision easy. The detection of the animal is done using CNN by converting images into greyscale, segmented and masked in the pre-processing stage. Then using Computer Vision technique, bounding boxes are formed around animals and count is also printed with the use of CV library. The whole project can tell which animal and count of those animals present. The proposed system uses the algorithms namely AlexNet, ResNet, Maxpooling 2D.

KeyWords : Computer Vision, Machine Learning, Twilio, CNN