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 want to count the number of pedestrians in the video using a deep neural network.

Keyphrases: crowd counting video

Dataset description:
COVIDx: An open access benchmark dataset comprising of 13,975 CXR images across 13,870 patient cases, with the largest number of publicly available COVID-19 positive cases to the best of the authors' knowledge.
Chickenpox Cases in Hungary: Chickenpox Cases in Hungary is a spatio-temporal dataset of weekly chickenpox (childhood disease) cases from Hungary. It can be used as a longitudinal dataset for benchmarking the predictive performance of spatiotemporal graph neural network architectures.
COWC: The Cars Overhead With Context (COWC) data set is a large set of annotated cars from overhead. It is useful for training a device such as a deep neural network to learn to detect and/or count cars.
Mall: The Mall is a dataset for crowd counting and profiling research. Its images are collected from publicly accessible webcam.
DiCOVA: The DiCOVA Challenge dataset is derived from the Coswara dataset, a crowd-sourced dataset of sound recordings from COVID-19 positive and non-COVID-19 individuals. The Coswara data is collected using a web-application2, launched in April-2020, accessible through the internet by anyone around the globe.
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: COVIDx  B: Chickenpox Cases in Hungary  C: COWC  D: Mall  E: DiCOVA  F: ImageNet
["Mall", "ImageNet"]