Liang Zhou – författare

Medical images can highlight differences between healthy tissue and unhealthy tissue and these images can then be assessed by a healthcare professional to identify the stage and spread of a disease so a treatment path can be established. With machine learning techniques becoming more prevalent in healthcare, algorithms can be trained to identify healthy or unhealthy tissues and quickly differentiate between the two. Statistical models can be used to process numerous images of the same type in a fraction of the time it would take a human to assess the same quantity, saving time and money in aiding practitioners in their assessment.This edited book discusses feature extraction processes, reviews deep learning methods for medical segmentation tasks, outlines optimisation algorithms and regularisation techniques, illustrates image classification and retrieval systems, and highlights text recognition tools, game theory, and the detection of misinformation for improving healthcare provision.Machine Learning in Medical Imaging and Computer Vision provides state of the art research on the integration of new and emerging technologies for the medical imaging processing and analysis fields. This book outlines future directions for increasing the efficiency of conventional imaging models to achieve better performance in diagnoses as well as in the characterization of complex pathological conditions.The book is aimed at a readership of researchers and scientists in both academia and industry in computer science and engineering, machine learning, image processing, and healthcare technologies and those in related fields.

This SpringerBrief discusses the most recent research in the field of multimedia QoE evaluation, with a focus on how to evaluate subjective multimedia QoE problems from objective techniques.

Urban Surface Thermal Environments: A Metropolitan Area Perspective presents a comprehensive exploration of urban heat dynamics through the perspectives of climate change, urbanization, green infrastructure, and two- and three-dimensional urban morphology.

In chapters 3, 4, and 5, the authors respectively propose three key techniques within the cross-modal communication architecture: cross-modal coding, cross-modal transmission and cross-modal signal recovery.

The objective of this SpringerBrief is to present security architectures and incentive mechanisms to realize system availability for D2D communications. D2D communications enable devices to communicate directly, improving resource utilization, enhancing user’s throughput, extending battery lifetime, etc. However, due to the open nature of D2D communications, there are two substantial technical challenges when applied to large-scale applications, that is, security and availability which is demonstrated in this book.This SpringerBrief proposes a secure data sharing protocol, which merges the advantages of public key cryptography and symmetric encryption, to achieve data security in D2D communications. Furthermore, a joint framework involving both the physical and application layer security technologies is proposed for multimedia service over D2D communications thus the scalable security service can be achieved without changing the current communication framework. Additionally, as the system availability largely depends on the cooperation degree of the users, a graph-theory based cooperative content dissemination scheme is proposed to achieve maximal Quality of Experience (QoE) with fairness and efficiency.This SpringerBrief will be a valuable resource for advanced-level students and researchers who want to learn more about cellular networks.