Given a short query with keyphrases about a research idea in 2017 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: A new theoretical and experimental study on the training of residual networks.

Keyphrases: image classification images

Dataset description:
Multi Task Crowd: Multi Task Crowd is a new 100 image dataset fully annotated for crowd counting, violent behaviour detection and density level classification.
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).
BDD100K: Datasets drive vision progress, yet existing driving datasets are impoverished in terms of visual content and supported tasks to study multitask learning for autonomous driving. Researchers are usually constrained to study a small set of problems on one dataset, while real-world computer vision applications require performing tasks of various complexities.
YCBInEOAT Dataset: A new dataset with significant occlusions related to object manipulation.

Options:- A: Multi Task Crowd  B: CIFAR-10  C: BDD100K  D: YCBInEOAT Dataset
CIFAR-10