Antonio Morales

Control and Systems Engineering · 2004–2013

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 23 citations into it; #1,552 of 8,257 by trust here, #631 by citations
• Computer Vision and Pattern Recognition — 20 citations into it
• Biomedical Engineering — 13 citations into it; #8,725 of 10,734 by trust here, #6,166 by citations
• Robotics & Control — 9 citations into it; #179 of 609 by trust here, #203 by citations
• Artificial Intelligence — 8 citations into it; #31,662 of 35,345 by trust here, #25,809 by citations
• Cognitive Neuroscience — 5 citations into it; #3,051 of 10,852 by trust here, #2,740 by citations

Whom Antonio Morales trusts overall

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

1. Martin A. Riedmiller
2. Antonio Bicchi
3. David G. Lowe
4. Peter K. Allen
5. Matei T. Ciocarlie
6. Paul A. Viola
7. Andrew T. Miller
8. Vijay R. Kumar
9. Shigeo Abe
10. Rosen Diankov

Who trusts Antonio Morales overall

1. Andy Zeng
2. Jeffrey Mahler
3. Lerrel Pinto
4. Daniel Kappler
5. Abhinav Kumar Gupta
6. Robert Paolini
7. Sergey Levine
8. Oliver Kroemer
9. Jeannette Bohg
10. A. Cousins

Papers from Antonio Morales's perspective

Ordered by how strongly the researchers Antonio Morales 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. ImageNet Large Scale Visual Recognition Challenge
8. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
9. Object recognition from local scale-invariant features
10. Going deeper with convolutions

Their papers

• Using Experience for Assessing Grasp Reliability (2004) — 80 citations
• OpenGRASP: A Toolkit for Robot Grasping Simulation (2010) — 145 citations
• Data-Driven Grasp Synthesis—A Survey (2013) — 1,118 citations