Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: I want to train a super deep residual network for image recognition.

Keyphrases: image recognition images

Dataset description:
Indian Pines: Indian Pines is a Hyperspectral image segmentation dataset. The input data consists of hyperspectral bands over a single landscape in Indiana, US, (Indian Pines data set) with 145×145 pixels.
BSD: BSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by Martin et al..
OST300: OST300 is an outdoor scene dataset with 300 test images of outdoor scenes, and a training set of 7 categories of images with rich textures.
CIFAR-10: The CIFAR-10 dataset (Canadian Institute for Advanced Research, 10 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images. The images are labelled with one of 10 mutually exclusive classes: airplane, automobile (but not truck or pickup truck), bird, cat, deer, dog, frog, horse, ship, and truck (but not pickup truck).

Options:- A: Indian Pines  B: BSD  C: OST300  D: CIFAR-10
CIFAR-10