Datasets.txt

Data sets die niet 100gb zijn, meer tussen de 20 en 1 gb. 

niet medisch:
https://www.kaggle.com/smeschke/four-shapes
https://www.kaggle.com/moltean/fruits
https://www.kaggle.com/thedownhill/art-images-drawings-painting-sculpture-engraving
https://www.kaggle.com/iarunava/happy-house-dataset
https://www.kaggle.com/google/tinyquickdraw
https://www.kaggle.com/prasunroy/natural-images

medisch:
https://www.kaggle.com/kmader/colorectal-histology-mnist
https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia
https://www.kaggle.com/skooch/ddsm-mammography
https://www.kaggle.com/kmader/skin-cancer-mnist-ham10000
https://www.kaggle.com/paultimothymooney/blood-cells


Paper source: https://arxiv.org/pdf/1810.05444.pdf
name,       methode,                  #img  #classes  used in paper:
STL-10      object recognition        100K  10        Schlegl et al. (2014)
Places      scene recognition         2.5M  205       Zhang et al. (2017) Du et al. (2018)
DTD         texture classification    5.6K  47        Ribeiro et al. (2017) Shi et al. (2018) (Christodoulidis et al., 2017)
ALOT        texture classification    28K   250       Ribeiro et al. (2017) (Christodoulidis et al., 2017)
KTH-TIPS    texture classification    810   10        Ribeiro et al. (2017) (Christodoulidis et al., 2017)
CIFAR-10    object classification     60K   10        Shin et al. (2016) Cha et al. (2017)
FMD         texture classification    1K    10        Christodoulidis et al. (2017)
KTB         texture classification    4.5K  27        Christodoulidis et al. (2017)
UIUC        texture classification    1K    25        Christodoulidis et al. (2017)
CALTECH-101 object recognition        9K    101       Ribeiro et al. (2017)
COREL-1000  scene recognition         1K    10        Ribeiro et al. (2017)
Kaggle-DR   image classification      35K   2         Menegola et al. (2017)
INbreast    breasr lesesion classi    410   2         Shi et al. (2018)
ICPR 2012   hr2-cell classification   1.5K  6         Lei et al. (2018)

https://github.com/sfikas/medical-imaging-datasets
some more...