Date of Award
Bachelor of Science in Applied Mathematics
The overall purpose of this study was to automate the manual process of tagging species found in camera trap images using machine learning. The basic design of this study was to implement a Convolutional Neural Network model in Python using the Keras and Tensorflow modules that learn to recognize patterns in images in order to classify what species is in a given image and to label it accordingly. Results of the analysis highlight the importance of a large sample size, the degree of accuracy according to various arguments in the model, effectiveness of multiple layers that include Max Pooling, and limitations due to processing capacity. Findings include a summary of classification accuracy at varying predictive probability thresholds.
Casey, Annie, "A Convolutional Neural Network Model for Species Classification of Camera Trap Images" (2018). Mathematics Undergraduate Theses. 8.