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: We propose a novel recurrent memo-rized attention model for interpretable and contextualized multi

Keyphrases: multi-label image recognition images

Dataset description:
IEMOCAP: Multimodal Emotion Recognition IEMOCAP The IEMOCAP dataset consists of 151 videos of recorded dialogues, with 2 speakers per session for a total of 302 videos across the dataset. Each segment is annotated for the presence of 9 emotions (angry, excited, fear, sad, surprised, frustrated, happy, disappointed and neutral) as well as valence, arousal and dominance.
PadChest: PadChest is a labeled large-scale, high resolution chest x-ray dataset for the automated exploration of medical images along with their associated reports. This dataset includes more than 160,000 images obtained from 67,000 patients that were interpreted and reported by radiologists at Hospital San Juan Hospital (Spain) from 2009 to 2017, covering six different position views and additional information on image acquisition and patient demography.
COCO: The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.
WHU: Created for MVS tasks and is a large-scale multi-view aerial dataset generated from a highly accurate 3D digital surface model produced from thousands of real aerial images with precise camera parameters.

Options:- A: IEMOCAP  B: PadChest  C: COCO  D: WHU
COCO