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: I have a CNN-based saliency prediction model to solve the saliency prediction task.

Keyphrases: saliency prediction images

Dataset description:
iSUN: iSUN is a ground truth of gaze traces on images from the SUN dataset. The collection is partitioned into 6,000 images for training, 926 for validation and 2,000 for test.
SALICON: The SALIency in CONtext (SALICON) dataset contains 10,000 training images, 5,000 validation images and 5,000 test images for saliency prediction. This dataset has been created by annotating saliency in images from MS COCO.
CAT2000: Includes 4000 images; 200 from each of 20 categories covering different types of scenes such as Cartoons, Art, Objects, Low resolution images, Indoor, Outdoor, Jumbled, Random, and Line drawings.
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.
Abalone: Predicting the age of abalone from physical measurements. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope -- a boring and time-consuming task.
ECSSD: The Extended Complex Scene Saliency Dataset (ECSSD) is comprised of complex scenes, presenting textures and structures common to real-world images. ECSSD contains 1,000 intricate images and respective ground-truth saliency maps, created as an average of the labeling of five human participants.

Options:- A: iSUN  B: SALICON  C: CAT2000  D: COCO  E: Abalone  F: ECSSD
["SALICON", "CAT2000", "COCO"]