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Animal Detection via Deep Learning by Ghazal Bilal is a document available to read on EtoBox.

The document describes using deep learning algorithms for animal detection. Specifically, it discusses using a convolutional neural network (CNN) model to automatically identify, count, and describe wild animals in camera trap images. CNNs are well-suited for this task as they can learn visual features from data without much pre-processing. The document also briefly reviews other techniques like template matching but selects CNNs due to their higher accuracy.

Author
Ghazal Bilal
Language
EN