Comparison of Deep Learning and Object-Based Image Classification Methods: Identification of Horses from RGB Imagery
The paper describes the utilisation of remotely sensed RGB data to support routine monitoring of horses in a natural environment on demand. Data are sensed using an unmanned aerial vehicle (UAV). UAVs provide very high spatial resolution data sensed at a low altitude on demand. Sensing is limited by weather conditions and legal rules only. Terrain does not need to be accessible. The article provides a comparison of several classification methods, namely object-based classification methods and Deep Learning classification. Namely Maximum Likelihood, Random Trees, Support Vector Machine (SVM), K-Nearest Neighbour (K-NN) and Deep Learning models U-Net and Deep Lab version 3. Manual classification is used as the reference method.
Authors
- Pavel Sedlák
- Jakub Jech
- Martin Krátký
- Tomáš Brunclík
Institutions
- University of Pardubice (CZ)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procs.2025.07.026
- Primary Topic
- Image Processing and 3D Reconstruction
- Type
- article
- Field-Weighted Citation Impact
- 0.00