Results 71 to 80 of about 6,825,217 (303)
Research on Object Panoramic 3D Point Cloud Reconstruction System Based on Structure From Motion
IEEE Access, 2022 3D reconstruction is the transformation of real objects into mathematical models. By using 3D models, we can observe the shape and measure the parameters, and help us to analyze the properties of objects.
Xuejing Zhang +8 more
doaj +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Virtual Reality & Intelligent HardwareEfficient three-dimensional (3D) building reconstruction from drone imagery often faces data acquisition, storage, and computational challenges because of its reliance on dense point clouds.
Xiongjie Yin, Jinquan He, Zhanglin Cheng
doaj +1 more source
Remote Sensing, 2021 Estimation of urban tree canopy parameters plays a crucial role in urban forest management. Unmanned aerial vehicles (UAV) have been widely used for many applications particularly forestry mapping.
Ebadat Ghanbari Parmehr, Marco Amati
doaj +1 more source
Why Is the Mechanism Underlying the Chiral‐Induced Selectivity Effect Still Challenging?
Advanced Materials, EarlyView.The chiral‐induced spin selectivity (CISS) effect is observed in many experimental configurations and for different materials. However, there are theoretical challenges in attempting to explain those results. A qualitative framework for explaining all the results is presented.
Ron Naaman, Yossi Paltiel
wiley +1 more source
3D Point Cloud Classification with ACGAN-3D and VACWGAN-GP
Turkish Journal of Electrical Engineering and Computer Sciences, 2023 Machine learning and deep learning techniques are widely used to make sense of 3D point cloud data which became ubiquitous and important due to the recent advances in 3D scanning technologies and other sensors. In this work, we propose two networks to predict the class of the input 3D point cloud: 3D Auxiliary Classifier Generative Adversarial Network (
Ergün, Onur, Sahillioglu, Yusuf
openaire +3 more sources
3D CITY MODELLING OF ISTANBUL BASED ON LIDAR DATA AND PANORAMIC IMAGES – ISSUES AND CHALLENGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 This paper describes the generation of 3D city modelling of LoD2 and LoD3 buildings based on 3D point clouds data and other auxiliary data for Istanbul city, Turkey.
G. Buyuksalih +4 more
doaj +1 more source
Semi-Supervised Semantic Segmentation Network for Point Clouds Based on 3D Shape
Applied Sciences, 2023 The semantic segmentation of point clouds has significant applications in fields such as autonomous driving, robot vision, and smart cities. As LiDAR technology continues to develop, point clouds have gradually become the main type of 3D data.
Liting Zhang, Kun Zhang
doaj +1 more source
Advanced Materials, EarlyView.The engineering of colloidal nanocrystals with complex compositions has emerged as a highly active area of research within nanomaterials science. This review covers key aspects of colloidal solid‐solution nanocrystal formation using pulsed laser irradiation.
Marina T. Candela +4 more
wiley +1 more source
Feature Based Particle Filter Registration of 3D Surface Models and its Application in Robotics [PDF]
, 2013 This work is focused on global registration of surface models such as homogeneous triangle meshes and point clouds. The investigated approach utilizes feature descriptors in order to assign correspondences between the data sets and to reduce complexity ...
Michael Suppa +9 more
core +1 more source