Fredrik K. Gustafsson
Computer Vision and Pattern Recognition · 2000–2023
A researcher in the Science corpus: 15 papers; trusts 921 researchers and is trusted by 40 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 210 citations into it
- Artificial Intelligence — 130 citations into it; #5,189 of 35,345 by trust here, #7,241 by citations
- Probabilistic & Bayesian Methods — 77 citations into it
- Aerospace Engineering — 44 citations into it; #2,557 of 6,421 by trust here, #1,291 by citations
- Evaluation & Benchmarks — 30 citations into it
- Electrical and Electronic Engineering — 26 citations into it; #5,116 of 16,539 by trust here, #7,892 by citations
- Generative Models — 26 citations into it
- Media Technology — 23 citations into it
Whom Fredrik K. Gustafsson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Diederik P. Kingma
- Radford M. Neal
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Arnaud Doucet
- Max Welling
- Ross B. Girshick
Who trusts Fredrik K. Gustafsson overall
- Fredrik Lindsten
- Simon S. Haykin
- Svante Björklund
- Thomas Bo Schön
- X. Rong Li
- C. Laoudias
- Giuseppe Bianchi
- Di Feng
- Ismail Güvenç
- Inseok Hwang
Papers from Fredrik K. Gustafsson's perspective
Ordered by how strongly the researchers Fredrik K. Gustafsson trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision (2019) — 349 citations
- The Eighth Visual Object Tracking VOT2020 Challenge Results (2020) — 345 citations
- How to Train Your Energy-Based Model for Regression (2020) — 44 citations
- Energy-Based Models for Deep Probabilistic Regression (2020) — 75 citations
- Particle filters for positioning, navigation, and tracking (2002) — 1,900 citations
- Particle Filter SLAM with High Dimensional Vehicle Model (2009) — 55 citations
- Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements (2005) — 993 citations
- Positioning using time-difference of arrival measurements (2003) — 389 citations
- Image Restoration with Mean-Reverting Stochastic Differential Equations (2023) — 318 citations
- Statistical Sensor Fusion (2013) — 413 citations
- Some Relations Between Extended and Unscented Kalman Filters (2012) — 367 citations
- Particle filter theory and practice with positioning applications (2010) — 750 citations
- Mobile Positioning Using Wireless Networks (2005) — 327 citations
- Marginalized particle filters for mixed linear/nonlinear state-space models (2005) — 693 citations
- Adaptive filtering and change detection (2000) — 1,192 citations