Given a short query with keyphrases about a research idea in 2019 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: Jointly learning feed-forward neural networks across a set of relevant but diverse datasets.

Keyphrases: multi-dataset learning images video

Dataset description:
NCBI Disease: The NCBI Disease corpus consists of 793 PubMed abstracts, which are separated into training (593), development (100) and test (100) subsets. The NCBI Disease corpus is annotated with disease mentions, using concept identifiers from either MeSH or OMIM.
CelebA: CelebFaces Attributes dataset contains 202,599 face images of the size 178×218 from 10,177 celebrities, each annotated with 40 binary labels indicating facial attributes like hair color, gender and age.
SI-SCORE: A synthetic dataset uses for a systematic analysis across common factors of variation.
ISTD: The Image Shadow Triplets dataset (ISTD) is a dataset for shadow understanding that contains 1870 image triplets of shadow image, shadow mask, and shadow-free image.

Options:- A: NCBI Disease  B: CelebA  C: SI-SCORE  D: ISTD
CelebA