Sandeep Kumar

Rohit Raja

Shilpa Rani

Shrikant Tiwari

Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms

The book focuses on the way that human beings and computers interact to ever increasing levels of both complexity and simplicity. Assuming very little knowledge, the book provides content on theory, cognition, design, evaluation, and user diversity. It aims to explain the underlying causes of the cognitive, social and organizational problems typically are devoted to descriptions of rehabilitation methods for specific cognitive processes. This book describes new algorithms for modeling accessible to cognitive scientists of all varieties. The book is inherently interdisciplinary, publishing original research in the fields of computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization, as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Machine learning research has been being carried out for a decade at international level in various applications. The new learning approach is mostly used in machine learning based cognitive applications. This will give direction for future research to scientists and researchers working in neuroscience, neuro-imaging, machine learning based brain mapping and modeling etc.

Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithm

K. Ramya Laxmi

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Shilpa Rani

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