At present, less than 30% of researchers worldwide are women. As an estimate, this number is even lower in the field of Signal Processing, with some sources indicating it could be around 10%. Long-standing biases and gender stereotypes are discouraging girls and women away from science related fields, and STEM research in particular. Science and gender equality are, however, essential to ensure sustainable development as highlighted by UNESCO. In order to change traditional mindsets, gender equality must be promoted, stereotypes defeated, and girls and women should be encouraged to pursue STEM careers. Frontiers in Signal Processing is proud to offer this platform to promote the work of women researchers and engineers, across all areas of Signal Processing. The work presented here highlights the diversity of research performed across the entire breadth of the Signal Processing landscape, and presents advances in theory, experiment and methodology with applications to compelling problems. This article collection is open for submissions across all sections of the journal, and new articles will be added as they are published. Please note: to be considered for this collection, the corresponding author should be a female researcher.

This book provides comprehensive, authoritative surveys covering the modeling, automatic detection, analysis, and synthesis of nonverbal social signals.

This book covers four sections such as artificial intelligence and machine learning; VLSI and signal processing; robotics and automation; and communications and networking. This book is a collection of selected papers presented at the First International Conference on Innovations in Signal Processing and Embedded Systems (ICISPES 2021), organized by MLR Institute of Technology, Hyderabad, India, during October 22–23, 2021. The topics covered are advanced communication technologies, IoT-based systems and applications, application AI in computer vision, natural language processing, reinforcement learning, ANN and deep neural networks, RNN, GAN, CNN and RBM, SOC, NOC design, VLSI and CAD/CAM, cross-layer design, fault tolerance and computation theories, FPGA in outer space, nanotechnology, semiconductor technology, signal and image processing, high-performance computing, pattern recognition and computer vision innovations in robotics, reconfigurable robots, and MEMS/NEMS.

This book presents the select proceedings of the International Conference on Automation, Signal Processing, Instrumentation and Control (i-CASIC) 2020. The book mainly focuses on emerging technologies in electrical systems, IoT-based instrumentation, advanced industrial automation, and advanced image and signal processing. It also includes studies on the analysis, design and implementation of instrumentation systems, and high-accuracy and energy-efficient controllers. The contents of this book will be useful for beginners, researchers as well as professionals interested in instrumentation and control, and other allied fields.

Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing. Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time. - Presents cognitive signal processing methodologies that are related to challenging image processing application domains - Provides the state-of-the-art in cognitive signal processing approaches in the area of big-data image processing - Focuses on other technical aspects and alternatives to traditional tools, algorithms and methodologies - Discusses various real-time case studies and implemented works

Biomedical signal processing in the medical field has helped optimize patient care and diagnosis within medical facilities. As technology in this area continues to advance, it has become imperative to evaluate other ways these computation techniques could be implemented. Computational Tools and Techniques for Biomedical Signal Processing investigates high-performance computing techniques being utilized in hospital information systems. Featuring comprehensive coverage on various theoretical perspectives, best practices, and emergent research in the field, this book is ideally suited for computer scientists, information technologists, biomedical engineers, data-processing specialists, and medical physicists interested in signal processing within medical systems and facilities.

This book provides a breadth of innovative and impactful research in the field of telecommunications led by women investigators. Topics covered include satellite communications, cognitive radars, remote sensing sensor networks, quantum Internet, and cyberspace. These topics touch on many of the challenges facing the world today and these solutions by women researchers are valuable for their technical excellence and their non-traditional perspective. As an important part of the Women in Engineering and Science book series, the work highlights the contribution of women leaders in telecommunications, inspiring women and men, girls and boys to enter and apply themselves to secure our future in.

Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. - Gives advanced methods in signal processing - Includes machine and deep learning methods - Presents experimental case studies

This book constitutes the refereed proceedings of the 5th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2019, held in Trivandrum, India, in December 2019. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 63 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

This book focuses on current and innovative technologies in perinatal medicine, specifically the period from the third trimester of pregnancy up to one month after birth. It follows the Second International Summer School on Technologies and Signal Processing in Perinatal Medicine (TSPPM 2021) and includes a number of the master lectures presented at the school. The book aims to provide an overview of current data processing and machine learning approaches, with clear indications and exhaustive presentations on research trends in the field, written by top scientists and researchers. It also presents the underlying clinical aspects and ethico-legal issues associated with the adoption of these technologies, particularly artificial intelligence tools. Innovative Technologies and Signal Processing in Perinatal Medicine: Volume 2 provides students, researchers, and practitioners with the knowledge necessary to carry out basic and applied research on the development of perinatal medicine medical devices with a particular emphasis on software design and development.