YOLOv3-Based Matching Approach for Roof Region Detection from Drone Images

YOLOv3-Based Matching Approach for Roof Region Detection from Drone Images

Due to the large data volume, the UAV image stitching and matching suffers from high computational cost. The traditional feature extraction algorithms—such as Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), and Oriented FAST Rotated BRIEF (ORB)—require heavy computation...

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Bibliographic Details
Main Authors: Chia-Cheng Yeh, Yang-Lang Chang, Mohammad Alkhaleefah, Pai-Hui Hsu, Weiyong Eng, Voon-Chet Koo, Bormin Huang, Lena Chang
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Remote Sensing
Subjects:
image matching
deep learning
YOLOv3
roof region detection
drone images
high-performance computing
Online Access:https://www.mdpi.com/2072-4292/13/1/127

Internet

https://www.mdpi.com/2072-4292/13/1/127

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