3D deep learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D deep learning, covering a wide range of research topics and applications. It collates the most recent research advances in 3D deep learning, including algorithms and applications, with a focus on efficient methods to tackle the key technical challenges in current 3D deep learning research and adoption, therefo...

"Exploring the World – Europe & America" presents in a bilingual English-Chinese edition, from a Chinese perspective, a synthetic profile of 9 countries (United Kingdom, France, Germany, Italy, Spain, Russia, United States, Canada, Mexico) in the fields of arts and culture, gastronomy or sports.

Over the past few decades, the field of machine learning has made remarkable strides, surpassing human performance in tasks like voice and object recognition, as well as mastering various complex games. Despite these accomplishments, a critical challenge remains: the absence of general intelligence. Achieving artificial general intelligence (AGI) requires the development of learning agents that can continually adapt and learn throughout their existence, a concept known as lifelong learning...

Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficult...

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP.Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjun...

Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning appl...

Advances in Biosystems investigates the latest techniques for evaluating, detecting, measuring, and enhancing the functional bioactivities, chemical composition, and physicochemical characteristics of animal, plant, and environmental biosystems. This comprehensive, interdisciplinary handbook provides detailed explanations for tracking functional molecules during various biological processes, along with practical methodologies for both laboratory and industrial applications. Sections cover ...

This volume provides food researchers with advanced destructive and non-destructive techniques for measuring the chemical composition, functional bioactivities physicochemical changes, and explaining the functional mechanisms for facilitating the tracking of the functional molecules during the different industrial processes. Chapters guide readers through sample preparation emerging extraction technologies protocols analytical methodologies for phytochemicals profiling, multi way models in...

This book constitutes refereed proceedings of the Second International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format.The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various a...

This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift and foundation models. It offers an in-depth look at cutting-edge techniques and methodologies, using advance algorithms that are transforming time series analysis across industries. The authors highlight the use AI models, particularly those based on deep learning, to study the sequence of data points collected at successive points in time. In the study of the use...

Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department’s history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional...

Biological and clinical studies provide valuable insight into the causes and potential cures of disease. Using statistics and data mining and other computational approaches, bioinformatics researchers can provide the medical community with ground-breaking discoveries that change how we perceive and treat these illnesses. Computational Knowledge Discovery for Bioinformatics Research discusses the most significant research and latest practices in computational knowledge discovery approaches ...