Ji Zhang

Aerospace Engineering · Robotics: Science and Systems Conference · 2014–2017

A researcher in the Science corpus: 3 papers; trusts 106 researchers and is trusted by 53 researchers here, as inferred from the citation graph.

Subfields

• Aerospace Engineering — 39 citations into it; #254 of 6,421 by trust here, #1,543 by citations
• Computer Vision and Pattern Recognition — 31 citations into it; #3,545 of 21,575 by trust here, #8,409 by citations
• Geology — 14 citations into it; #128 of 687 by trust here, #551 by citations
• Electrical and Electronic Engineering — 9 citations into it; #2,192 of 16,539 by trust here, #12,727 by citations
• Evaluation & Benchmarks — 5 citations into it

Whom Ji Zhang trusts overall

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

1. M. Bosse
2. Andreas Geiger
3. Robert Zlot
4. François Pomerleau
5. Szymon Rusinkiewicz
6. Christopher Evans
7. Radu Bogdan Rusu
8. Philip Lenz
9. Robert Andersen
10. C. Levine

Who trusts Ji Zhang overall

1. Tixiao Shan
2. Jens Behley
3. Tong Qin
4. Brendan Englot
5. Jean-Emmanuel Deschaud
6. Joel Janai
7. César Debeunne
8. Cyrill Stachniss
9. Haoyang Ye
10. Sanjiv Singh

Papers from Ji Zhang's perspective

Ordered by how strongly the researchers Ji Zhang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Distinctive Image Features from Scale-Invariant Keypoints
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• LOAM: Lidar Odometry and Mapping in Real-time (2014) — 3,191 citations
• Visual-lidar odometry and mapping: low-drift, robust, and fast (2015) — 701 citations
• Low-drift and real-time lidar odometry and mapping (2017) — 760 citations