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Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
LSUN Bedrooms
The dataset used in the paper is the LSUN bedrooms dataset, a large-scale image dataset. -
Deep Image: Scaling up image recognition
Deep Image: Scaling up image recognition -
Holy Places Dataset
A dataset of images of holy places (Kaaba, Zamzam, Maqam Ibrahim) for training a deep learning model. -
Learning Multiple Layers of Features from Tiny Images
The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.
