The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area.
This book is designed to provide rich research hub for researchers, teachers, and students to ease research hassle/challenges.
This book explores the cognitive plausibility of computational language models and why it’s an important factor in their development and evaluation.
This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications.
This book covers a variety of advanced communications technologies that can be used to analyze medical data and can be used to diagnose diseases in clinic... Læs mere
This book surveys the state of the art in explainable and interpretable reinforcement learning (RL) as relevant for robotics. While RL... Læs mere
This book provides a comprehensive overview of Human Activity Detection or Recognition (HADR) systems.
We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data.
This book highlights contemporary state of research in multi-disciplinary areas in Physics, Biomedical Sciences, Chemical Engineering, Mechanical Engineering, Computer Science/Engineering, Life Sciences, and Healthcare.
This book gathers outstanding research papers presented at the 7th International Joint Conference on Advances in Computational Intelligence (IJCACI 2023), held in hybrid mode at South Asian University, New Delhi, India during October 14–15, 2023.
It also includes the progress in signal processing to process the normal... Læs mere