Concepedia

Training Data Labeling

Training Data Labeling is the systematic process of annotating raw field boundary data with categorical or spatially explicit class labels to enable supervised learning models to recognize and delineate boundaries accurately within geospatial datasets.

529

Publications

40.7K

Citations

1.9K

Authors

584

Institutions

Publications per year

2017–2026

311

Parents

Publications

529

Practical Black-Box Attacks against Machine Learning

Nicolas Papernot, Patrick McDaniel, Ian Goodfellow et al. · 2017 · 3.5K citations

, , +10

A brief introduction to weakly supervised learning

Zhi‐Hua Zhou · National Science Review · 2017 · 1.9K citations · Full text

, , +9

Understanding deep learning requires rethinking generalization

Chiyuan Zhang, Samy Bengio, Moritz Hardt et al. · arXiv (Cornell University) · 2016 · 1.1K citations · Full text

, , +13

Unsupervised Salience Learning for Person Re-identification

Rui Zhao, Wanli Ouyang, Xiaogang Wang · 2013 · 1K citations

, , +15

Preparing Medical Imaging Data for Machine Learning

Martin J. Willemink, Wojciech A. Koszek, Cailin Hardell et al. · Radiology · 2020 · 976 citations · Full text

, , +13

1–5 of 529

Authors

1.9K

  1. AR
    Alexander Ratner

    Stanford University, United States

    4 publications · 1.2K citations

    4

    h-index

  2. HK
    Harpreet Kaur

    The University of Texas at Austin, United States

    3 publications · 273 citations

    3

    h-index

  3. SH
    Stefan Hinterstoißer

    Technical University of Munich, Germany

    3 publications · 213 citations

    3

    h-index

  4. GA
    Gernot A. Fink

    TU Dortmund University, Germany

    3 publications · 58 citations

    3

    h-index

  5. YS
    Yeeleng S. Vang

    University of California, Irvine, United States

    3 publications · 89 citations

    3

    h-index

1–5 of 1.9K

Institutions

584

  1. Carnegie Mellon University

    Pittsburgh, United States

    19 h-index

    58 publications

    3.3K citations

  2. Google (United States)

    Mountain View, United States

    13 h-index

    36 publications

    5.7K citations

  3. Stanford University

    Stanford, United States

    11 h-index

    38 publications

    17.1K citations

  4. The University of Texas at Austin

    Austin, United States

    9 h-index

    22 publications

    1.3K citations

  5. Microsoft (United States)

    Redmond, United States

    8 h-index

    23 publications

    2.1K citations

  6. University of Washington

    Seattle, United States

    8 h-index

    18 publications

    2.3K citations

  7. Chinese Academy of Sciences

    Beijing, China

    8 h-index

    22 publications

    1.4K citations

  8. Nanyang Technological University

    Singapore, Singapore

    7 h-index

    19 publications

    1K citations

1–8 of 584

Venues

  1. arXiv (Cornell University)

    Repository · 38 publications · 2.5K citations

    22

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 1.1K citations

    11

    h-index

  3. Sensors

    8 publications · 242 citations

    8

    h-index

  4. Remote Sensing

    6 publications · 470 citations

    6

    h-index

  5. 6

    h-index

1–5