Data FusionPoint cloud processingMultiple viewpoint 3D reconstruction has been used in recent years to create accurate complete scenes and objects used for various applications. This is to overcome limitations of single viewpoint 3D digital imaging such as occlusion within the scene during the ...
FedAvg reduces the communication overhead by allowing multiple SGD steps between each communication round. In this manner, instead of just sending a gradient update after each SGD step, FedAvg allows clients to send local parameters estimates at the end of each communication round. As a result, ...
To ensure the reliability of the data, various techniques can be employed, such as data quality control and preprocessing, cloud detection algorithms, and remote sensing data fusion technology. These approaches serve to mitigate the influence of cloud cover and terrain variation, thereby enhancing the...
Since the character-based HMM is stroke-order dependent, multiple models are often required for the characters with stroke order variations or large shape variations [[31], [32]]. In HMM-based recognition, the task of recognition is to decode the observation sequence (points or line segments)...
We design a content and structure importance evaluation function based on the attribute information of the dataset to fuse the output results of two channels and propose a dual channel fusion module under the influence of attributes to improve the accuracy of search results and make the model more...
Forest Canopy Height (FCH) is a crucial parameter that offers valuable insights into forest structure. Spaceborne LiDAR missions provide accurate FCH measu
This model fuses data from light detection and ranging (LiDAR), inertial measurement unit (IMU), and cameras dynamically, enhancing the flexibility of the fusion process. Finally, multiple primitive features are adaptively fused within the factor graph optimization, utilizing a sliding window approach....
To address this, we propose a point cloud completion network that integrates a dynamic weighted fusion of multi-scale features with Transformer enhancements. Our approach incorporates three key innovations: a multi-layer perceptron fused with EdgeConv to enhance local feature extraction for small-sample...
To address this, we propose a point cloud completion network that integrates a dynamic weighted fusion of multi-scale features with Transformer enhancements. Our approach incorporates three key innovations: a multi-layer perceptron fused with EdgeConv to enhance local feature extraction for small-sample...
POINT cloudOPTICAL radarLIDARMULTICASTING (Computer networks)YIELD strength (Engineering)ALGORITHMSSPACE-based radarThis paper proposes a point-by-point weighted fusion algorithm based on an improved random sample consensus (RANSAC) and inverse distance weighting to address the issue of low-resolution ...