Given a short query with keyphrases about a research idea in 2015 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: Learning 15 billion parameters on HPC architectures.

Keyphrases: large-scale deep learning image video

Dataset description:
Icentia11K: Public ECG dataset of continuous raw signals for representation learning containing 11 thousand patients and 2 billion labelled beats.
CLUECorpus2020: CLUECorpus2020 is a large-scale corpus that can be used directly for self-supervised learning such as pre-training of a language model, or language generation. It has 100G raw corpus with 35 billion Chinese characters, which is retrieved from Common Crawl.
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.
Semantic3D: Semantic3D is a point cloud dataset of scanned outdoor scenes with over 3 billion points. It contains 15 training and 15 test scenes annotated with 8 class labels.

Options:- A: Icentia11K  B: CLUECorpus2020  C: ImageNet  D: Semantic3D
ImageNet