Guobiao Yao
Biographic Data
| ID | 6310868 |
|---|---|
| NAME | Guobiao Yao |
| GIVEN NAMES | Guobiao |
| FAMILY NAME | Yao |
| SIGNATURE | YAO G |
| AFFILIATIONS | Shandong Jianzhu University |
| ORCID | 0000-0001-6305-4514 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 5 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Multi-View Three-Dimensional Reconstruction Based on Feature Enhancement and Weight Optimization Network
Aiming to address the issue that existing multi-view stereo reconstruction methods have insufficient adaptability to the repetitive and weak textures in multi-view images, this paper proposes a three-dimensional (3D) reconstruction algorithm based on Feature Enhancement and Weight Optimization MVSNet (Abbreviated as FEWO-MVSNet). To obtain accurate and detailed global and local features, we first develop an adaptive feature enhancement approach t…
MSA-UNet
An accurate and reliable extraction of building structures from high-resolution (HR) remote sensing images is an important research topic in 3D cartography and smart city construction. However, despite the strong overall performance of recent deep learning models, limitations remain in handling significant variations in building scales and complex architectural forms, which may lead to inaccurate boundaries or difficulties in extracting small or …
Automatic Production of Deep Learning Benchmark Dataset for Affine-Invariant Feature Matching
To promote the development of deep learning for feature matching, image registration, and three-dimensional reconstruction, we propose a method of constructing a deep learning benchmark dataset for affine-invariant feature matching. Existing images often have large viewpoint differences and areas with weak texture, which may cause difficulties for image matching, with respect to few matches, uneven distribution, and single matching texture. To so…
Spatio-temporal evolution of urban built-up areas and analysis of driving factors —A comparison of typical cities in north and south China
Improved Indoor Fingerprinting Localization Method Using Clustering Algorithm and Dynamic Compensation
Many indoor fingerprinting localization methods are based on signal-domain distances with large localization error and low stability. An improved fingerprinting localization method using a clustering algorithm and dynamic compensation was proposed. In the offline stage, the fingerprint database was built and clustered based on offline hybrid distance and an affinity propagation clustering algorithm. Furthermore, clusters were adjusted using trans…
Detecting the true urban polycentric pattern of Chinese cities in morphological dimensions
Improved Indoor Fingerprinting Localization Method Using Clustering Algorithm and Dynamic Compensation
Many indoor fingerprinting localization methods are based on signal-domain distances with large localization error and low stability. An improved fingerprinting localization method using a clustering algorithm and dynamic compensation was proposed. In the offline stage, the fingerprint database was built and clustered based on offline hybrid distance and an affinity propagation clustering algorithm. Furthermore, clusters were adjusted using trans…
Detecting the true urban polycentric pattern of Chinese cities in morphological dimensions
Spatio-temporal evolution of urban built-up areas and analysis of driving factors —A comparison of typical cities in north and south China
Automatic Production of Deep Learning Benchmark Dataset for Affine-Invariant Feature Matching
To promote the development of deep learning for feature matching, image registration, and three-dimensional reconstruction, we propose a method of constructing a deep learning benchmark dataset for affine-invariant feature matching. Existing images often have large viewpoint differences and areas with weak texture, which may cause difficulties for image matching, with respect to few matches, uneven distribution, and single matching texture. To so…
Multi-View Three-Dimensional Reconstruction Based on Feature Enhancement and Weight Optimization Network
Aiming to address the issue that existing multi-view stereo reconstruction methods have insufficient adaptability to the repetitive and weak textures in multi-view images, this paper proposes a three-dimensional (3D) reconstruction algorithm based on Feature Enhancement and Weight Optimization MVSNet (Abbreviated as FEWO-MVSNet). To obtain accurate and detailed global and local features, we first develop an adaptive feature enhancement approach t…
MSA-UNet
An accurate and reliable extraction of building structures from high-resolution (HR) remote sensing images is an important research topic in 3D cartography and smart city construction. However, despite the strong overall performance of recent deep learning models, limitations remain in handling significant variations in building scales and complex architectural forms, which may lead to inaccurate boundaries or difficulties in extracting small or …
Artificial Intelligence (3 works) · Computer Science (3 works) · Advanced Neural Network Applications (2 works) · China (2 works) · Civil engineering (2 works) · Computer vision (2 works) · Demography (2 works) · Economic geography (2 works) · Feature extraction (2 works) · Geography (2 works)