Michael Trentini

Aerospace Engineering · 2016

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Aerospace Engineering — 47 citations into it; #5,434 of 6,421 by trust here, #4,945 by citations
• Computer Vision and Pattern Recognition — 31 citations into it
• Computer Networks and Communications — 18 citations into it
• Electrical and Electronic Engineering — 17 citations into it; #12,950 of 16,539 by trust here, #13,553 by citations
• Artificial Intelligence — 13 citations into it
• Ocean Engineering — 8 citations into it; #2,686 of 3,193 by trust here, #2,164 by citations
• Mechanical Engineering — 7 citations into it

Whom Michael Trentini trusts overall

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

1. Sebastian Thrun
2. Andrew Howard
3. Dirk Hähnel
4. Wolfram Burgard
5. Giorgio Grisetti
6. Ronald P. S. Mahler
7. Andrea Censi
8. Rainer Kümmerle
9. H. F. Durrant-Whyte
10. Frank Dellaert

Who trusts Michael Trentini overall

1. Jun Zhang

Papers from Michael Trentini's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet: A large-scale hierarchical image database
4. Distinctive Image Features from Scale-Invariant Keypoints
5. Gradient-based learning applied to document recognition
6. FastSLAM: a factored solution to the simultaneous localization and mapping problem (AAAI/IAAI)
7. Optimization of the simultaneous localization and map-building algorithm for real-time implementation (IEEE Trans. Robotics Autom.)
8. A Probabilistic On-Line Mapping Algorithm for Teams of Mobile Robots (Int. J. Robotics Res.)
9. Histograms of oriented gradients for human detection
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Multiple‐Robot Simultaneous Localization and Mapping: A Review (2016) — 313 citations