You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: Out-of-distribution detection.

Keyphrases: out-of-distribution detection images

Dataset description:
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).
ImageNet-R: ImageNet-R(endition) contains art, cartoons, deviantart, graffiti, embroidery, graphics, origami, paintings, patterns, plastic objects, plush objects, sculptures, sketches, tattoos, toys, and video game renditions of ImageNet classes. ImageNet-R has renditions of 200 ImageNet classes resulting in 30,000 images.
ClipShots: ClipShots is a large-scale dataset for shot boundary detection collected from Youtube and Weibo covering more than 20 categories, including sports, TV shows, animals, etc. In contrast to previous shot boundary detection datasets, e.g.
StreetHazards: StreetHazards is a synthetic dataset for anomaly detection, created by inserting a diverse array of foreign objects into driving scenes and re-render the scenes with these novel objects.
ROSTD: A dataset of 4K out-of-domain (OOD) examples for the publicly available dataset from (Schuster et al. 2019).
ImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.

Options:- A: CIFAR-10  B: ImageNet-R  C: ClipShots  D: StreetHazards  E: ROSTD  F: ImageNet
["CIFAR-10", "ImageNet"]