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. | |
CIFAR10/100 | 10/100 | Image classification | |
MNIST | 10 | Classification of handwritten digits | |
Pascal VOC | 20 | Image classification, segmentation, object detection | |
Microsoft COCO | 80 | Object detection, semantic segmentation | |
YFCC100M | 8M | Video and image understanding | |
YouTube-8M | 4716 | Video classification | |
UCF-101 | 101 | Human action detection | |
Kinetics | 400 | Human action detection | |
Google Open Images | 350 | Image classification, segmentation, object detection | |
CalTech101 | 101 | Classification | |
Labeled Faces in the Wild | – | Face recognition | |
MIT-67 scene dataset | 67 | Indoor scene recognition |