Jan Dirk Wegner
Computer Vision and Pattern Recognition · 2015–2022
A researcher in the Science corpus: 11 papers; trusts 769 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 169 citations into it; #12,587 of 21,575 by trust here, #7,092 by citations
- Artificial Intelligence — 55 citations into it
- Aerospace Engineering — 47 citations into it; #1,563 of 6,421 by trust here, #1,268 by citations
- Computational Mechanics — 35 citations into it
- Environmental Engineering — 35 citations into it; #988 of 5,479 by trust here, #747 by citations
- Geology — 30 citations into it; #165 of 687 by trust here, #151 by citations
- Media Technology — 25 citations into it
- Model Architectures — 25 citations into it
Whom Jan Dirk Wegner trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- David G. Lowe
- Karen Simonyan
- Yann LeCun
- Ross B. Girshick
- Diederik P. Kingma
- Yoshua Bengio
- Andrew Zisserman
Who trusts Jan Dirk Wegner overall
- Joel Janai
- Alexandre Boulch
- Nicolas Audebert
- Christopher Bongsoo Choy
- Jiazhou Chen
- Qingyong Hu
- Xiaohui Yuan
- Xiaoshui Huang
- Bertrand Le Saux
- Xavier Roynard
Papers from Jan Dirk Wegner's perspective
Ordered by how strongly the researchers Jan Dirk Wegner trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Large-Scale Semantic 3D Reconstruction: An Adaptive Multi-resolution Model for Multi-class Volumetric Labeling (2016) — 101 citations
- Classification With an Edge: Improving Semantic Image Segmentation with Boundary Detection (2016) — 665 citations
- SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS (2016) — 334 citations
- SEMANTIC SEGMENTATION OF AERIAL IMAGES IN URBAN AREAS WITH CLASS-SPECIFIC HIGHER-ORDER CLIQUES (2015) — 53 citations
- Learning Aerial Image Segmentation From Online Maps (2017) — 319 citations
- A high-resolution canopy height model of the Earth (2022) — 605 citations
- The Hessigheim 3D (H3D) Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and Textured Meshes from UAV LiDAR and Multi-View-Stereo (2021) — 134 citations
- Topological Map Extraction From Overhead Images (2018) — 192 citations
- The Perfect Match: 3D Point Cloud Matching With Smoothed Densities (2018) — 543 citations
- Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark (2017) — 825 citations
- FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY (2016) — 373 citations