IEEE

Dual Branch Graph Representation Learning-Based Approach for Next Point-of-Interest Recommendation

Abstract: Next Point-of-Interest (POI) recommendation, a sub-task of POI recommendation, focuses on predicting the next POI a user will visit, relying on the user’s sequential check-in history. In ...
IEEE

PointWavelet: Learning in Spectral Domain for 3-D Point Cloud Analysis

Abstract: With recent success of deep learning in 2-D visual recognition, deep-learning-based 3-D point cloud analysis has received increasing attention from the community, especially due to the rapid ...
IEEE

Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features

Abstract: Learning through a point cloud is attractive be-cause a point cloud contains geometric data and can help robots understand environments in a robust manner. However, a point cloud is sparse, ...
IEEE

3D Urban Buildings Extraction Based on Airborne LiDAR and Photogrammetric Point Cloud Fusion According to U-Net Deep Learning Model Segmentation

Abstract: The LiDAR and photogrammetric point clouds fusion procedure for building extraction according to U-Net deep learning model segmentation is provided and tested. Firstly, an initial ...
IEEE

Deep Learning-Based Point Cloud Compression: An In-Depth Survey and Benchmark

Abstract: With the maturity of 3D capture technology, the explosive growth of point cloud data has burdened the storage and transmission process. Traditional hybrid point cloud compression (PCC) tools ...
IEEE

Revolutionizing Point Cloud Classification with Multiview Self-Supervised Learning

Abstract: Self-supervised models are shaping the future of point cloud processing by minimizing reliance on labeled data and addressing the challenges associated with point cloud annotation.
GitHub

NumberFormatException in TaskCache #8885

java.lang.NumberFormatException: For input string: "-1,-1" at java.base/java.lang.NumberFormatException.forInputString(NumberFormatException.java:67) at java.base ...
IEEE

DSANet: Dynamic and Structure-Aware GCN for Sparse and Incomplete Point Cloud Learning

Abstract: Learning 3-D structures from incomplete point clouds with extreme sparsity and random distributions is a challenge since it is difficult to infer topological connectivity and structural ...
Hosted on MSN

New Mexico State University offering tours of Apache Point Observatory

More for You The Commander in Chief Is Not Okay Federal employee taken into custody following "active shooter hoax" at NJ's largest military base China reacts to Donald Trump's new tariffs Chaos at ...
IEEE

Deep Learning Deployment on Big Data Infrastructure Using Apache Spark (Case Study: COVID-19 Detection Using X-Ray Images)

Abstract: It is possible to use GPU (Graphic Processing Unit) to increase deep learning performance. This requires us to invest in separate GPUs, which can be relatively expensive. However, if we ...
IEEE

Deep Learning-Based Point Cloud Reconstruction Method for CAD Models

Abstract: In the field of 3D modeling, point cloud reconstruction technology is a crucial step in generating high-precision 3D models from collected point cloud data. Traditional reconstruction ...
IEEE

Unsupervised Degradation Representation Learning for Unpaired Restoration of Images and Point Clouds

Abstract: Restoration tasks in low-level vision aim to restore high-quality (HQ) data from their low-quality (LQ) observations. To circumvents the difficulty of acquiring paired data in real scenarios ...