Gregory D. Hager

Active 1986–2026

424
Papers
28,383
Citations
77
h-index
281
i10-index

Citations

Citations per year for Gregory D. Hager1962: 1 citations1979: 2 citations1986: 3 citations1988: 3 citations1989: 1 citations1991: 4 citations1992: 16 citations1993: 8 citations1994: 22 citations1995: 34 citations1996: 55 citations1997: 87 citations1998: 130 citations1999: 184 citations2000: 219 citations2001: 205 citations2002: 248 citations2003: 324 citations2004: 363 citations2005: 428 citations2006: 423 citations2007: 491 citations2008: 480 citations2009: 477 citations2010: 476 citations2011: 560 citations2012: 582 citations2013: 577 citations2014: 671 citations2015: 568 citations2016: 630 citations2017: 651 citations2018: 712 citations2019: 999 citations2020: 1,122 citations2021: 1,303 citations2022: 1,195 citations2023: 1,127 citations2024: 1,232 citations2025: 985 citations2026: 208 citations1963–1978: no citations, so these years are not shown1980–1985: no citations, so these years are not shown1987: no citations, so this year is not shown1990: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 4,113 citing papers, 22.9% of this breakdownChina: 2,786 citing papers, 15.5% of this breakdownGermany: 1,139 citing papers, 6.3% of this breakdownUnited Kingdom: 1,094 citing papers, 6.1% of this breakdownFrance: 1,074 citing papers, 6% of this breakdownCanada: 730 citing papers, 4.1% of this breakdownItaly: 678 citing papers, 3.8% of this breakdownJapan: 677 citing papers, 3.8% of this breakdownAustralia: 457 citing papers, 2.5% of this breakdownSpain: 424 citing papers, 2.3% of this breakdownSouth Korea: 391 citing papers, 2.2% of this breakdownIndia: 365 citing papers, 2% of this breakdown
0%22.9%Other 22.5%

Fields

  • Computer Science51.7%
  • Engineering25.4%
  • Medicine15%
  • Neuroscience1.8%
  • Psychology1.2%
  • Biochemistry, Genetics and Molecular Biology0.7%
  • Other4.2%

Topics

  • Advanced Vision and Imaging9.2%
  • Robotics and Sensor-Based Localization7.7%
  • Video Surveillance and Tracking Methods3.6%
  • Advanced Image and Video Retrieval Techniques3.4%
  • Surgical Simulation and Training3.3%
  • Human Pose and Action Recognition3.3%
  • Other69.5%

Coauthors

All papers

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  1. Temporal Convolutional Networks for Action Segmentation and Detection

    Authors: , , , , - IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 cited by 2,040

  2. Temporal Convolutional Networks: A Unified Approach to Action Segmentation

    Authors: , , , - Lecture notes in computer science, ECCV Workshops (3) 2016 cited by 882

  3. Large-scale pancreatic cancer detection via non-contrast CT and deep learning

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Chengwei Shao, Yu Shi, Qi Zhang, Tingbo Liang, Ling Zhang, Jianping Lu - Nature Medicine 2023 cited by 302

  4. Surgical data science – from concepts toward clinical translation

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Minu D. Tizabi, Martin Wagner, Gregory D. Hager, Thomas Neumuth, Nicolas Padoy, Justin Collins, Ines Gockel, Jan Goedeke, Daniel A. Hashimoto, Luc Joyeux, Kyle Lam, Daniel Leff, Amin Madani, Hani J. Marcus, Ozanan R. Meireles, Alexander Seitel, Doğu Teber, Frank Ückert, Beat P. Müller‐Stich, Pierre Jannin, Stefanie Speidel - 2022 cited by 332

  5. Surgical data science for next-generation interventions

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , - Nature Biomedical Engineering 2017 cited by 534

  6. A tutorial on visual servo control

    Authors: , , - IEEE Transactions on Robotics and Automation, IEEE Trans. Robotics Autom. 1996 cited by 3,501

  7. Deep learning: RNNs and LSTM

    Authors: , - Elsevier eBooks 2019 cited by 255

  8. On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward

    Authors: , , , , , , , , , , , , , , , , - National Academy of Sciences, Proceedings of the National Academy of Sciences 2020 cited by 157

  9. A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery

    Authors: , , , , , , , , , - IEEE Transactions on Biomedical Engineering, IEEE Trans. Biomed. Eng. 2017 cited by 289

  10. Semantic Image Manipulation Using Scene Graphs

    Authors: , , , , , , - IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020 cited by 118

  11. Fast and Globally Convergent Pose Estimation from Video Images

    Authors: , , - IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Trans. Pattern Anal. Mach. Intell. 2000 cited by 873

  12. Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses

    Authors: , , , , , , - IEEE International Conference on Computer Vision (ICCV) 2017 cited by 178

  13. Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review

    Authors: , , , - Journal of NeuroInterventional Surgery 2019 cited by 299

  14. Impact of data on generalization of AI for surgical intelligence applications

    Authors: , , , , , , , - Scientific Reports 2020 cited by 89

  15. A Delphi consensus statement for digital surgery

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Mark Slack, Myles J. Smith, Naeem Soomro, Stefanie Speidel, Danail Stoyanov, Henry S. Tilney, Martin Wagner, Ara Darzi, James Kinross, Sanjay Purkayastha - npj Digital Medicine, npj Digit. Medicine 2022 cited by 84

  16. CoSTAR: Instructing Collaborative Robots with Behavior Trees and Vision

    Authors: , , , , - IEEE International Conference on Robotics and Automation (ICRA) 2017 cited by 171

  17. SAGES consensus recommendations on an annotation framework for surgical video

    Authors: , , , , , , , , , , , - Surgical Endoscopy 2021 cited by 108

  18. SAGE: SLAM with Appearance and Geometry Prior for Endoscopy

    Authors: , , , , , - International Conference on Robotics and Automation (ICRA) 2022 cited by 44

  19. Evaluation and Stability Analysis of Video-Based Navigation System for Functional Endoscopic Sinus Surgery on In Vivo Clinical Data

    Authors: , , , , , , - IEEE Transactions on Medical Imaging, IEEE Trans. Medical Imaging 2018 cited by 92

  20. Intent-Aware Pedestrian Prediction for Adaptive Crowd Navigation

    Authors: , , - IEEE International Conference on Robotics and Automation (ICRA) 2020 cited by 54

  21. Surgical data science - from concepts toward clinical translation

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Minu Dietlinde Tizabi, Martin Wagner, Gregory D. Hager, Thomas Neumuth, Nicolas Padoy, Justin Collins, Ines Gockel, Jan Goedeke, Daniel A. Hashimoto, Luc Joyeux, Kyle Lam, Daniel Richard Leff, Amin Madani, Hani J. Marcus, Ozanan R. Meireles, Alexander Seitel, Dogu Teber, Frank Ückert, Beat P. Müller-Stich, Pierre Jannin, Stefanie Speidel - Medical Image Analysis, Medical Image Anal. 2021 cited by 43

  22. Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions

    Authors: , , , - IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009 cited by 617

  23. Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration

    Authors: , , , , , , - IEEE International Conference on Robotics and Automation (ICRA) 2020 cited by 39

  24. Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques

    Authors: , , , , , , , , , - JAMA Network Open 2019 cited by 120