Abstract
A system for individual identification of The Royal Bengal Tigers (Panthera tigris) is absolutely necessary not only for monitoring the population of tigers but also for saving the precious lives of those workers whose job is to count the exact number of tigers present in a particular region like Sundarban in West Bengal, India. In this paper, a solution has been proposed for individual identification of Bengal Tigers using an autonomous/manually controlled drone. In the proposed system, the drone camera will search for the tigers using a Tiger Detection Model and then the flank (the body part which contains the stripes) of the detected tiger will be passed through a Fine-tuned state-of-art network. The system based on deep CNN will detect the uncommon features for individual counting of the tiger in a particular forest. The proposed system will enhance the accuracy of tiger detection technique that will be followed by the human experts. It also reduces the risk of accidents relating to animal attacks.
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Kishore, T., Jha, A., Kumar, S., Bhattacharya, S., Sultana, M. (2021). Deep CNN Based Automatic Detection and Identification of Bengal Tigers. In: Dutta, P., Mandal, J.K., Mukhopadhyay, S. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2021. Communications in Computer and Information Science, vol 1406. Springer, Cham. https://doi.org/10.1007/978-3-030-75529-4_15
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