ImageNet

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 133 articles )

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  1. 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
  2. Haghighat, Ehsan; Juanes, Ruben: SciANN: a keras/tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks (2021)
  3. 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
  4. Hao, Jie; Zhu, William: Architecture self-attention mechanism: nonlinear optimization for neural architecture search (2021)
  5. Hua, Michelle; Gao, Mingqi; Zhong, Zichun: SCN: dilated silhouette convolutional network for video action recognition (2021)
  6. Kwanyoung Park, Hyunseok Oh, Youngki Lee: VECA : A Toolkit for Building Virtual Environments to Train and Test Human-like Agents (2021) arXiv
  7. Li, Zhihan; Fan, Yuwei; Ying, Lexing: Multilevel fine-tuning: closing generalization gaps in approximation of solution maps under a limited budget for training data (2021)
  8. Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao: Face.evoLVe: A High-Performance Face Recognition Library (2021) arXiv
  9. Sven Kreiss, Lorenzo Bertoni, Alexandre Alahi: OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association (2021) arXiv
  10. Tuyls, Karl; Omidshafiei, Shayegan; Muller, Paul; Wang, Zhe; Connor, Jerome; Hennes, Daniel; Graham, Ian; Spearman, William; Waskett, Tim; Steel, Dafydd; Luc, Pauline; Recasens, Adria; Galashov, Alexandre; Thornton, Gregory; Elie, Romuald; Sprechmann, Pablo; Moreno, Pol; Cao, Kris; Garnelo, Marta; Dutta, Praneet; Valko, Michal; Heess, Nicolas; Bridgland, Alex; Pérolat, Julien; De Vylder, Bart; Eslami, S. M. Ali; Rowland, Mark; Jaegle, Andrew; Munos, Remi; Back, Trevor; Ahamed, Razia; Bouton, Simon; Beauguerlange, Nathalie; Broshear, Jackson; Graepel, Thore; Hassabis, Demis: Game plan: what AI can do for football, and what football can do for AI (2021)
  11. Urbaniak, Ilona; Wolter, Marcin: Quality assessment of compressed and resized medical images based on pattern recognition using a convolutional neural network (2021)
  12. Zejiang Shen, Ruochen Zhang, Melissa Dell, Benjamin Charles Germain Lee, Jacob Carlson, Weining Li: LayoutParser Toolkit Document Image (2021) arXiv
  13. Zöller, Marc-André; Huber, Marco F.: Benchmark and survey of automated machine learning frameworks (2021)
  14. Bullock, Joseph; Luccioni, Alexandra; Pham, Katherine Hoffman; Lam, Cynthia Sin Nga; Luengo-Oroz, Miguel: Mapping the landscape of artificial intelligence applications against COVID-19 (2020)
  15. Calder, Jeff; Slepčev, Dejan: Properly-weighted graph Laplacian for semi-supervised learning (2020)
  16. Carlsson, Gunnar; Gabrielsson, Rickard Brüel: Topological approaches to deep learning (2020)
  17. Chen, Ruidian; He, Jingsong: Two-stage training method of retinanet for bird’s nest detection (2020)
  18. Chen, Ruizhi; Li, Ling: Analyzing and accelerating the bottlenecks of training deep SNNs with backpropagation (2020)
  19. Christoph Heindl, Lukas Brunner, Sebastian Zambal, Josef Scharinger: BlendTorch: A Real-Time, Adaptive Domain Randomization Library (2020) arXiv
  20. Daryanavard, Sama; Porr, Bernd: Closed-loop deep learning: generating forward models with backpropagation (2020)

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Further publications can be found at: http://image-net.org/about-publication