Industry

Lyft
X5 Retail Group
MedHub
Recursion
Everypixel
Neuromation

Deep learning research

Albumentations is widely used in research areas related to computer vision and deep learning. If you find this library useful for your research, please consider citing Albumentations: Fast and Flexible Image Augmentations:
@Article{info11020125,
    AUTHOR = {Buslaev, Alexander and Iglovikov, Vladimir I. and Khvedchenya, Eugene and Parinov, Alex and Druzhinin, Mikhail and Kalinin, Alexandr A.},
    TITLE = {Albumentations: Fast and Flexible Image Augmentations},
    JOURNAL = {Information},
    VOLUME = {11},
    YEAR = {2020},
    NUMBER = {2},
    ARTICLE-NUMBER = {125},
    URL = {https://www.mdpi.com/2078-2489/11/2/125},
    ISSN = {2078-2489},
    DOI = {10.3390/info11020125}
}

List of papers that cite Albumentations

- NYQ Abderrahim, S Abderrahim
57. Benchmark for generic product detection: a strong baseline for dense object detection
- S Varadarajan, S Kant, MM Srivastava
- M Potanin, D Dimitrov, A Shonenkov, V Bataev
- D Wu, Y Chen, X Qi, Y Jian, W Chen, R Xiao
100. The Study of Improving the Accuracy of Convolutional Neural Networks in Face Recognition Tasks
- N Andriyanov, V Dementev
- X Yibin
- L Chang, W Zhuang, R Wu, S Feng, H Liu, J Yu
- HEB CASS
170. Deep Learning for Skin Lesion Classification: Augment, Train, and Ensemble
- M Genaev, E Skolotneva, E Gultyaeva, E Orlova
- D Lacalle, HA Castro-Abril, T Randelovic
- 王丽芳, 张程程, 秦品乐, 蔺素珍, 高媛, 窦杰亮
- 杨必胜, 宗泽亮, 陈驰, 孙文鹿, 米晓新, 吴唯同
- 林成创, 单纯, 赵淦森

Machine learning competitions


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