ImageNet is an image dataset organized according to the WordNet hierarchy. Each meaningful concept in WordNet, possibly described by multiple words or word phrases, is called a ”synonym set” or ”synset”. There are more than 100,000 synsets in WordNet, majority of them are nouns (80,000+). In ImageNet, we aim to provide on average 1000 images to illustrate each synset. Images of each concept are quality-controlled and human-annotated. In its completion, we hope ImageNet will offer tens of millions of cleanly sorted images for most of the concepts in the WordNet hierarchy.

References in zbMATH (referenced in 483 articles )

Showing results 1 to 20 of 483.
Sorted by year (citations)

1 2 3 ... 23 24 25 next

  1. Adcock, Ben; Dexter, Nick: The gap between theory and practice in function approximation with deep neural networks (2021)
  2. Ao, Wenqi; Li, Wenbin; Qian, Jianliang: A data and knowledge driven approach for SPECT using convolutional neural networks and iterative algorithms (2021)
  3. Cauchois, Maxime; Gupta, Suyash; Duchi, John C.: Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction (2021)
  4. Celledoni, Elena; Ehrhardt, Matthias J.; Etmann, Christian; Owren, Brynjulf; Schönlieb, Carola-Bibiane; Sherry, Ferdia: Equivariant neural networks for inverse problems (2021)
  5. Chen, Tianbo; Sun, Ying; Li, Ta-Hsin: A semi-parametric estimation method for the quantile spectrum with an application to earthquake classification using convolutional neural network (2021)
  6. Chi, Heng; Zhang, Yuyu; Tang, Tsz Ling Elaine; Mirabella, Lucia; Dalloro, Livio; Song, Le; Paulino, Glaucio H.: Universal machine learning for topology optimization (2021)
  7. Christopher P. Bridge, Chris Gorman, Steven Pieper, Sean W. Doyle, Jochen K. Lennerz, Jayashree Kalpathy-Cramer, David A. Clunie, Andriy Y. Fedorov, Markus D. Herrmann: Highdicom: A Python library for standardized encoding of image annotations and machine learning model outputs in pathology and radiology (2021) arXiv
  8. De Loera, Jesús A.; Haddock, Jamie; Ma, Anna; Needell, Deanna: Data-driven algorithm selection and tuning in optimization and signal processing (2021)
  9. Effland, Alexander; Kobler, Erich; Pock, Thomas; Rajković, Marko; Rumpf, Martin: Image morphing in deep feature spaces: theory and applications (2021)
  10. Fan, Jianqing; Ma, Cong; Zhong, Yiqiao: A selective overview of deep learning (2021)
  11. Fresca, Stefania; Dede’, Luca; Manzoni, Andrea: A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs (2021)
  12. Gambella, Claudio; Ghaddar, Bissan; Naoum-Sawaya, Joe: Optimization problems for machine learning: a survey (2021)
  13. Gao, Yu; Zhang, Kai: Machine learning based data retrieval for inverse scattering problems with incomplete data (2021)
  14. Gordon, Andrew S. (ed.); Miller, Rob (ed.); Morgenstern, Leora (ed.); Turán, György (ed.): Preface (2021)
  15. Gossmann, Alexej; Pezeshk, Aria; Wang, Yu-Ping; Sahiner, Berkman: Test data reuse for the evaluation of continuously evolving classification algorithms using the area under the receiver operating characteristic curve (2021)
  16. Guillaume Jaume, Pushpak Pati, Valentin Anklin, Antonio Foncubierta, Maria Gabrani: HistoCartography: A Toolkit for Graph Analytics in Digital Pathology (2021) arXiv
  17. Guo, Rui; Zhou, Yong; Zhao, Jiaqi; Yao, Rui; Liu, Bing; Zhang, Xunhui: Unsupervised spatial-awareness attention-based and multi-scale domain adaption network for point cloud classification (2021)
  18. Guo, Zhenfei; Bai, Ruixiang; Lei, Zhenkun; Jiang, Hao; Liu, Da; Zou, Jianchao; Yan, Cheng: CPINet: parameter identification of path-dependent constitutive model with automatic denoising based on CNN-LSTM (2021)
  19. Haghighat, Ehsan; Juanes, Ruben: SciANN: a keras/tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks (2021)
  20. Haiping Lu, Xianyuan Liu, Robert Turner, Peizhen Bai, Raivo E Koot, Shuo Zhou, Mustafa Chasmai, Lawrence Schobs: PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python (2021) arXiv

1 2 3 ... 23 24 25 next

Further publications can be found at: