Application of mask R-CNN for building detection in UAV remote sensing images.

ABSTRACT: This study aims to tackle the challenges of low accuracy in building feature extraction and insufficient details in three-dimensional (3D) modeling faced by traditional methods, particularly in complex backgrounds. To address these issues, a method for building feature extraction based on Mask Region-Convolutional Neural Network (Mask R-CNN) is proposed. This approach combines deep learning techniques with aerial images to ensure precise and efficient automatic detection and feature extraction. Urban building images are captured through aerial photography, and building outlines are annotated to create a comprehensive dataset of building features. The Mask R-CNN-based method efficiently processes and classifies the features of the dataset, generating candidate regions for further analysis.

SUBMITTER: Hou T 

PROVIDER: S-EPMC11467628 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature