ETD

An Analysis of Object Detection Systems for the Automatic Detection and Localization of Basking Rattlesnakes in Images

Public Deposited

The study of how prairie rattlesnakes, a common species of reptiles across the United States, regulate their body temperature is essential to human efforts to conserve such species and maintain ecological balance. The development of object detection systems has the potential of accelerating such a study by reducing human efforts to manually detect the presence of snakes in large collections of videos and images taken by camera traps. In this paper, we experiment with YOLO, a single stage object detection model, and Faster R-CNN, a multi-stage object detection model, on a dataset of snake images taken at a site in Colorado, United States. The accuracy of each model is then evaluated using both quantitative and qualitative measures and several suggestions are made to improve the performance of the models for practical applications.


MLA citation style (9th ed.)

Vo, Hoang Viet. An Analysis of Object Detection Systems for the Automatic Detection and Localization of Basking Rattlesnakes In Images. . 2022. dickinson.hykucommons.org/concern/etds/7116cf67-5249-4ab5-81aa-647fe63b9053?q=2022.

APA citation style (7th ed.)

V. H. Viet. (2022). An Analysis of Object Detection Systems for the Automatic Detection and Localization of Basking Rattlesnakes in Images. https://dickinson.hykucommons.org/concern/etds/7116cf67-5249-4ab5-81aa-647fe63b9053?q=2022

Chicago citation style (CMOS 17, author-date)

Vo, Hoang Viet. An Analysis of Object Detection Systems for the Automatic Detection and Localization of Basking Rattlesnakes In Images. 2022. https://dickinson.hykucommons.org/concern/etds/7116cf67-5249-4ab5-81aa-647fe63b9053?q=2022.

Note: These citations are programmatically generated and may be incomplete.

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