Animal/Object Identification Using Deep Learning on Raspberry Pi
In this paper, we have explained how to implement a Convolutional Neural Network(CNN) to detect and classify an animal/object from an image. By using the computational capabilities of a device known as Raspberry Pi, which has a relatively lower processing power and an infinitesimal small GPU, we classify the object provided to the CNN. An image is fed to Raspberry Pi, wherein we run a Python-based program with some dependencies, viz. TensorFlow, etc., to identify the animal/object from the image and classify it in appropriate category. We have tried to show that deep learning concepts like convolutional neural networks, and other such computation intensive programs can be implemented on an inexpensive and relatively less powerful device.
KeywordsAnimal identification Object identification Deep learning Raspberry Pi Convolutional neural networks
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