The Vertebrate Integrative Physiology (VIP) lab monitors the population of northern elephant seals at the largest mainland breeding colony, located at Piedras Blancas (San Simeon, CA). As the population expands, more human-seal interactions and conflicts over land use occur. The VIP lab's work informs California State Parks and helps with the management of the rookery. Currently, members of the VIP lab fly a drone over the beaches, capture multiple images, and manually count the seals, which takes around 14 to 21 hours of analysis per survey. Machine learning methods such as Convolutional Neural Networks (CNN) and Region-based Convolutional Neural Networks (RCNN) have been shown to quickly and accurately determine the count but require lots of data, which is not feasible for this task due to the 79 available beach images. By dividing larger beach images into smaller sub-images, it is possible to generate more data, facilitating the use of deep learning techniques. This thesis outlines a pipeline to use these sub-images and determine the seal count of a beach image.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-4554 |
| Date | 01 September 2024 |
| Creators | Kharwa, Kaanan |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
Page generated in 0.0025 seconds