Cargando…
3D Object Reconstruction from Imperfect Depth Data Using Extended YOLOv3 Network
State-of-the-art intelligent versatile applications provoke the usage of full 3D, depth-based streams, especially in the scenarios of intelligent remote control and communications, where virtual and augmented reality will soon become outdated and are forecasted to be replaced by point cloud streams...
Autores principales: | Kulikajevas, Audrius, Maskeliūnas, Rytis, Damaševičius, Robertas, Ho, Edmond S. L. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180802/ https://www.ncbi.nlm.nih.gov/pubmed/32260316 http://dx.doi.org/10.3390/s20072025 |
Ejemplares similares
-
Reconstruction of 3D Object Shape Using Hybrid Modular Neural Network Architecture Trained on 3D Models from ShapeNetCore Dataset
por: Kulikajevas, Audrius, et al.
Publicado: (2019) -
Auto-Refining Reconstruction Algorithm for Recreation of Limited Angle Humanoid Depth Data
por: Kulikajevas, Audrius, et al.
Publicado: (2021) -
HUMANNET—A Two-Tiered Deep Neural Network Architecture for Self-Occluding Humanoid Pose Reconstruction
por: Kulikajevas, Audrius, et al.
Publicado: (2021) -
Detection of sitting posture using hierarchical image composition and deep learning
por: Kulikajevas, Audrius, et al.
Publicado: (2021) -
Lightweight Deep Learning Model for Assessment of Substitution Voicing and Speech after Laryngeal Carcinoma Surgery
por: Maskeliūnas, Rytis, et al.
Publicado: (2022)