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: An unsupervised method to merge over-partitioned clusters.

Keyphrases: merging clusters images

Dataset description:
ModelNet: The ModelNet40 dataset contains synthetic object point clouds. As the most widely used benchmark for point cloud analysis, ModelNet40 is popular because of its various categories, clean shapes, well-constructed dataset, etc.
MVTecAD: MVTec AD is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection. It contains over 5000 high-resolution images divided into fifteen different object and texture categories.
DUC 2004: The DUC2004 dataset is a dataset for document summarization. Is designed and used for testing only.
UPIQ: Contains over 4,000 images created by realigning and merging existing HDR and standard-dynamic-range (SDR) datasets.
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: ModelNet  B: MVTecAD  C: DUC 2004  D: UPIQ  E: ImageNet
["ModelNet", "ImageNet"]