The objective of this thesis is to explore Deep Learning algorithms for classifying high-resolution images. While most deep learning algorithms focus on relatively low-resolution imagery (under 400×400 pixels), very high-resolution image classification poses unique challenges. These images occur in pathology and remote sensing, but here we focus on the classification of invasive plant species. We aimed to develop a computer vision system that can provide geo-coordinates of the locations of invasive plants by processing Google Map Street View images at using finite computational resources. We explore six methods for classifying these images and compare them. Our results could significantly impact the management of invasive plant species, which pose both economic and ecological threats.
Library of Congress Subject Headings
Neural networks (Computer science); Machine learning; Image processing--Digital techniques; Image analysis; Panoramas--Classification
Computer Science (MS)
Department, Program, or Center
Computer Science (GCCIS)
Sharma, Deepak, "Exploring Deep Neural Network Models for Classification of High-resolution Panoramas" (2019). Thesis. Rochester Institute of Technology. Accessed from
RIT – Main Campus