Fashion MNIST

From HandWiki
Short description: Popular MNIST alternative machine learning dataset of fashion images

The Fashion MNIST dataset is a large freely available database of fashion images that is commonly used for training and testing various machine learning systems.[1][2] Fashion-MNIST was intended to serve as a replacement for the original MNIST database for benchmarking machine learning algorithms, as it shares the same image size, data format and the structure of training and testing splits.[3]

The dataset contains 70,000 28x28 grayscale images of fashion products from 10 categories from a dataset of Zalando article images, with 7,000 images per category.[1] The training set consists of 60,000 images and the test set consists of 10,000 images. The dataset is commonly included in standard machine learning libraries.[4]

History

The set of images in the Fashion MNIST database was created in 2017 to pose a more challenging classification task than the simple MNIST digits data, which saw performance reaching upwards of 99.7%.[1]

The GitHub repository has collected collected over 4000 stars and is referred to more than 400 repositories, 1000 commits and 7000 code snippets.[5]

Numerous machine learning algorithms[6] have used the dataset as a benchmark,[7][8][9][10] with the top algorithm[11] achieving 96.91% accuracy in 2020 according to the benchmark rankings website.[12] The dataset was also used as a benchmark in the 2018 Science paper using all optical hardware to classify images at the speed of light.[13] Google, University of Cambridge, IBM Research, Université de Montréal, and Peking University are the repositories most published institutions as of 2021.[citation needed]

See also

References

  1. ↑ 1.0 1.1 1.2 Xiao, Han; Rasul, Kashif; Vollgraf, Roland (2017-09-15). "Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms". arXiv:1708.07747 [cs.LG].
  2. ↑ Shenwai, Tanushree (2021-09-07). "A New Google AI Research Study Discovers Anomalous Data Using Self Supervised Learning" (in en-US). https://www.marktechpost.com/2021/09/07/a-new-google-ai-research-study-discovers-anomalous-data-using-self-supervised-learning/. 
  3. ↑ "Fashion-MNIST: Year In Review · Han Xiao Tech Blog - Neural Search & AI Engineering" (in en). https://hanxiao.io/2018/09/28/Fashion-MNIST-Year-In-Review/. 
  4. ↑ "Basic classification: Classify images of clothing | TensorFlow Core" (in en). https://www.tensorflow.org/tutorials/keras/classification. 
  5. ↑ "Build software better, together" (in en). https://github.com/search?q=fashion-mnist. 
  6. ↑ "Papers using Fashion-MNIST (till 09.18)" (in en-US). https://docs.google.com/spreadsheets/d/1cGX7Juedn_KVUgjDk298v5uUjc_wPk930tKyEoZhTQM/edit?usp=embed_facebook. 
  7. ↑ Meshkini, Khatereh; Platos, Jan; Ghassemain, Hassan (2020). Kovalev, Sergey; Tarassov, Valery; Snasel, Vaclav et al.. eds. "An Analysis of Convolutional Neural Network for Fashion Images Classification (Fashion-MNIST)" (in en). Proceedings of the Fourth International Scientific Conference "Intelligent Information Technologies for Industry" (IITI'19). Advances in Intelligent Systems and Computing (Cham: Springer International Publishing) 1156: 85–95. doi:10.1007/978-3-030-50097-9_10. ISBN 978-3-030-50097-9. https://link.springer.com/chapter/10.1007/978-3-030-50097-9_10. 
  8. ↑ Kayed, Mohammed; Anter, Ahmed; Mohamed, Hadeer (February 2020). "Classification of Garments from Fashion MNIST Dataset Using CNN LeNet-5 Architecture". 2020 International Conference on Innovative Trends in Communication and Computer Engineering (ITCE): 238–243. doi:10.1109/ITCE48509.2020.9047776. ISBN 978-1-7281-4801-4. https://ieeexplore.ieee.org/document/9047776. 
  9. ↑ Bhatnagar, Shobhit; Ghosal, Deepanway; Kolekar, Maheshkumar H. (December 2017). "Classification of fashion article images using convolutional neural networks". 2017 Fourth International Conference on Image Information Processing (ICIIP): 1–6. doi:10.1109/ICIIP.2017.8313740. ISBN 978-1-5090-6733-6. https://ieeexplore.ieee.org/document/8313740. 
  10. ↑ Kadam, Shivam S.; Adamuthe, Amol C.; Patil, Ashwini B. (2020). "CNN Model for Image Classification on MNIST and Fashion-MNIST Dataset". Journal of Scientific Research 64 (2): 374–384. doi:10.37398/JSR.2020.640251. https://www.bhu.ac.in/research_pub/jsr/Volumes/JSR_64_02_2020/51.pdf. 
  11. ↑ Tanveer, Muhammad Suhaib; Khan, Muhammad Umar Karim; Kyung, Chong-Min (2020-06-16). "Fine-Tuning DARTS for Image Classification". arXiv:2006.09042 [cs.CV].
  12. ↑ "Papers with Code - Fashion-MNIST Benchmark (Image Classification)" (in en). https://paperswithcode.com/sota/image-classification-on-fashion-mnist. 
  13. ↑ Lin, Xing; Rivenson, Yair; Yardimci, Nezih T.; Veli, Muhammed; Luo, Yi; Jarrahi, Mona; Ozcan, Aydogan (2018-09-07). "All-optical machine learning using diffractive deep neural networks" (in en). Science 361 (6406): 1004–1008. doi:10.1126/science.aat8084. ISSN 0036-8075. PMID 30049787. Bibcode: 2018Sci...361.1004L. https://www.science.org/doi/10.1126/science.aat8084. 

External links




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