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Snake Image Classification using Siamese Networks

Research into deep learning models suitable for small data sets is still in an immature state since it has received less attention from the machine learning community. Identifying a snake species using images, is a classification problem which has a number of medical, educational and safety-related importance but no large data set. Due to the lack of large data sets and difficulty in collecting such data set, no one has applied deep learning algorithms, to solve this problem. In this paper, we explored the applicability of single shot learning techniques along with deep neural networks to solve the snake image classification problem. By using a convolutional architecture, we were able to achieve strong results and did a comparative analysis with human results.