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Ended Face Detection and Cast Grouping in Movies Using ErdosRenyi Clustering Sou Young Jin1, Hang Su1, Chris Stauffer2, and Erik LearnedMiller1 1 College of Information and Computer Sciences, University

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What is end-to-end face detection?

End-to-end face detection is a process of detecting faces in an image or video using a single neural network without the need for additional post-processing steps.

Who is required to file end-to-end face detection?

End-to-end face detection can be utilized by software developers, computer vision researchers, and companies looking to incorporate face detection technology into their applications.

How to fill out end-to-end face detection?

To fill out end-to-end face detection, one needs to train a neural network model on a dataset of labeled face images and then deploy the model to detect faces in new images or videos.

What is the purpose of end-to-end face detection?

The purpose of end-to-end face detection is to automate the process of detecting and identifying faces in images or videos, enabling various applications such as facial recognition, surveillance, and photography.

What information must be reported on end-to-end face detection?

The information reported on end-to-end face detection includes the location of detected faces, confidence scores for each detection, and any metadata associated with the detected faces.

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