Fusion of visible and thermal images improves automated detection and classification of animals for drone surveys.

ABSTRACT: Visible and thermal images acquired from drones (unoccupied aircraft systems) have substantially improved animal monitoring. Combining complementary information from both image types provides a powerful approach for automating detection and classification of multiple animal species to augment drone surveys. We compared eight image fusion methods using thermal and visible drone images combined with two supervised deep learning models, to evaluate the detection and classification of white-tailed deer (Odocoileus virginianus), domestic cow (Bos taurus), and domestic horse (Equus caballus). We classified visible and thermal images separately and compared them with the results of image fusion. Fused images provided minimal improvement for cows and horses compared to visible images alone, likely

SUBMITTER: Krishnan BS 

PROVIDER: S-EPMC10300091 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature