Given a short query with keyphrases about a research idea in 2014 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: Fractional Max Pooling - Improve Classification Accuracy.

Keyphrases: image classification images

Dataset description:
LITIS Rouen: The LITIS-Rouen dataset  is a dataset for audio scenes. It consists of 3026 examples of 19 scene categories.
HMDB51: The HMDB51 dataset is a large collection of realistic videos from various sources, including movies and web videos. The dataset is composed of 6,766 video clips from 51 action categories (such as “jump”, “kiss” and “laugh”), with each category containing at least 101 clips.
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).
LAReQA: A challenging new benchmark for language-agnostic answer retrieval from a multilingual candidate pool.

Options:- A: LITIS Rouen  B: HMDB51  C: CIFAR-10  D: LAReQA
CIFAR-10