Dana Kulic

Control and Systems Engineering · 2008–2017

A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 26 citations into it; #2,895 of 8,257 by trust here, #3,255 by citations
• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it; #9,847 of 21,575 by trust here, #13,815 by citations
• Social Psychology — 16 citations into it; #5,494 of 15,694 by trust here, #4,240 by citations
• Cognitive Neuroscience — 10 citations into it
• Model Architectures — 8 citations into it
• Natural Language Processing — 5 citations into it

Whom Dana Kulic trusts overall

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

1. Sylvain Calinon
2. Aude Gemma Billard
3. Lawrence R. Rabiner
4. Giacomo Rizzolatti
5. Graham W. Taylor
6. Michael I. Jordanzoubin
7. Anil K. Jain
8. Tetsuya Ogata
9. Geoffrey E. Hinton
10. Tetsunari Inamura

Who trusts Dana Kulic overall

1. Seyed Mohammad Khansari-Zadeh
2. Luiza Mici
3. Aude Gemma Billard
4. Sylvain Calinon
5. Moritz Tenorth
6. Takayuki Osa
7. German Ignacio Parisi
8. Jan Bandouch
9. Przemyslaw A. Lasota
10. Hyojin Chin

Papers from Dana Kulic's perspective

Ordered by how strongly the researchers Dana Kulic 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. Long Short-Term Memory
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Attention is All you Need (Neural Information Processing Systems)
8. GENERATIVE ADVERSARIAL NETS
9. ImageNet Large Scale Visual Recognition Challenge
10. ImageNet: A large-scale hierarchical image database

Their papers

• Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains (2008) — 233 citations
• Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots (2009) — 3,069 citations
• Incremental learning of full body motion primitives and their sequencing through human motion observation (2012) — 248 citations
• Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks (2017) — 844 citations
• Human Movement Understanding [TC Spotlight] (2015) — 10 citations