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Table 5 Benchmark datasets

From: Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Dataset

Num. of classes

Applications

Link to dataset

ImageNet

1000

Image classification, object localization, object detection, etc.

http://www.image-net.org/

CIFAR10/100

10/100

Image classification

https://www.cs.toronto.edu/~kriz/cifar.html

MNIST

10

Classification of handwritten digits

http://yann.lecun.com/exdb/mnist/

Pascal VOC

20

Image classification, segmentation, object detection

http://host.robots.ox.ac.uk/pascal/VOC/voc2012/

Microsoft COCO

80

Object detection, semantic segmentation

https://cocodataset.org/#home

YFCC100M

8M

Video and image understanding

http://projects.dfki.unikl.de/yfcc100m/

YouTube-8M

4716

Video classification

https://research.google.com/youtube8m/

UCF-101

101

Human action detection

https://www.crcv.ucf.edu/data/UCF101.php

Kinetics

400

Human action detection

https://deepmind.com/research/open-source/kinetics

Google Open Images

350

Image classification, segmentation, object detection

https://storage.googleapis.com/openimages/web/index.html

CalTech101

101

Classification

http://www.vision.caltech.edu/Image_Datasets/Caltech101/

Labeled Faces in the Wild

–

Face recognition

http://vis-www.cs.umass.edu/lfw/

MIT-67 scene dataset

67

Indoor scene recognition

http://web.mit.edu/torralba/www/indoor.htm