Steven L. Waslander

Computer Vision and Pattern Recognition · 2004–2023

A researcher in the Science corpus: 13 papers; trusts 815 researchers and is trusted by 50 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 188 citations into it; #4,312 of 21,575 by trust here, #4,193 by citations
• Artificial Intelligence — 86 citations into it
• Aerospace Engineering — 71 citations into it; #752 of 6,421 by trust here, #591 by citations
• Evaluation & Benchmarks — 43 citations into it; #2,133 of 3,147 by trust here, #2,903 by citations
• Automotive Engineering — 33 citations into it; #2,183 of 3,081 by trust here, #2,332 by citations
• Probabilistic & Bayesian Methods — 19 citations into it
• Environmental Engineering — 18 citations into it; #1,059 of 5,479 by trust here, #550 by citations
• Computational Mechanics — 14 citations into it

Whom Steven L. Waslander trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Diederik P. Kingma
6. Yoshua Bengio
7. Richard S. Sutton
8. Yann LeCun
9. Ilya Sutskever
10. Radford M. Neal

Who trusts Steven L. Waslander overall

1. S. Microtechnique
2. Daniel Mellinger
3. Vijay R. Kumar
4. Haitham Bou-Ammar
5. Sergei Lupashin
6. Shaoshuai Shi
7. Dorsa Sadigh
8. Nathan Michael
9. G. Hoffmann
10. Claire Jennifer Tomlin

Papers from Steven L. Waslander's perspective

Ordered by how strongly the researchers Steven L. Waslander trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Joint 3D Proposal Generation and Object Detection from View Aggregation (2017) — 1,597 citations
• Categorical Depth Distribution Network for Monocular 3D Object Detection (2021) — 641 citations
• In Defense of Classical Image Processing: Fast Depth Completion on the CPU (2018) — 337 citations
• LMDrive: Closed-Loop End-to-End Driving with Large Language Models (2023) — 378 citations
• Canadian Adverse Driving Conditions dataset (2020) — 305 citations
• A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving (2020) — 314 citations
• Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perception (2019) — 121 citations
• Unlimited Road-scene Synthetic Annotation (URSA) Dataset (2018) — 23 citations
• Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering (2009) — 498 citations
• Quadrotor Helicopter Trajectory Tracking Control (2008) — 371 citations
• Quadrotor Helicopter Flight Dynamics and Control: Theory and Experiment (2007)
• Multi-agent quadrotor testbed control design: integral sliding mode vs. reinforcement learning (2005) — 314 citations
• The Stanford testbed of autonomous rotorcraft for multi agent control (STARMAC) (2004) — 373 citations