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: We present an approach to transfer learning which involves training an auxiliary model to learn the relevant features and a target

Keyphrases: image classification images

Dataset description:
KLEJ: The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding task. Key benchmark features:   It contains a diverse set of tasks from different domains and with different objectives.
EMBER: A labeled benchmark dataset for training machine learning models to statically detect malicious Windows portable executable files. The dataset includes features extracted from 1.1M binary files: 900K training samples (300K malicious, 300K benign, 300K unlabeled) and 200K test samples (100K malicious, 100K benign).
BanglaLekhaImageCaptions: This dataset consists of images and annotations in Bengali. The images are human annotated in Bengali by two adult native Bengali speakers.
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.
Syn2Real: Syn2Real, a synthetic-to-real visual domain adaptation benchmark meant to encourage further development of robust domain transfer methods. The goal is to train a model on a synthetic "source" domain and then update it so that its performance improves on a real "target" domain, without using any target annotations.
Places: The Places dataset is proposed for scene recognition and contains more than 2.5 million images covering more than 205 scene categories with more than 5,000 images per category.

Options:- A: KLEJ  B: EMBER  C: BanglaLekhaImageCaptions  D: ImageNet  E: Syn2Real  F: Places
["ImageNet", "Places"]