Search Results for author:
Found 3 papers, 0 papers with code
Synthetic Data Generation and Deep Learning for the Topological Analysis of 3D Data
This research uses deep learning to estimate the topology of manifolds represented by sparse, unordered point cloud scenes in 3D.
Topology Estimation of Simulated 4D Image Data by Combining Downscaling and Convolutional Neural Networks
Four-dimensional image-type data can quickly become prohibitively large, and it may not be feasible to directly apply methods, such as persistent homology or convolutional neural networks, to determine the topological characteristics of these data because they can encounter complexity issues.
Count-guided Weakly Supervised Localization Based on Density Map
In this paper, we generalize WSL to counting machines that apply convolutional neural networks (CNN) and density maps for counting.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
