A groundbreaking, urgent report from the front lines of "dirty work"-the work that society considers essential but morally compromised.

This book explores the innovations, disruptions and changes that are required to adapt in a fast-evolving landscape due to the extraordinary circumstances triggered by the COVID-19 pandemic. Recognized experts from around the world share their research and professional experience on how the working environment, as well as the world around them, have changed due to the pandemic.

This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.