1st Edition
Research Advances in Intelligent Computing Volume 2
As the computers and other machines have been developed, researchers and scientists have worked very hard to increase their capacity to carry out a variety of jobs. Thus, computers' capabilities in terms of varied working areas, adaptable duties, processing speed, and smaller size are all increasing exponentially every day. We are currently competing to develop machines or computers that are as intelligent as people. Making a computer or piece of software think like a smart human being is what artificial intelligence (AI) is all about. AI is influenced by the study of the human brain, namely how people make decisions, learn, and respond when attempting to solve any problems. The findings of this study serve as the foundation for creating intelligent systems and software, or intelligent computing (IC). An IC system is capable of learning, reasoning, solving problems, perceiving, and using language. AI and other cutting-edge approaches that provide a system intelligence are used in IC systems. Virtually every branch of computer science has seen the use of intelligent computing, including networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Today, IC is also used to resolve a variety of complicated problems in many different fields, including disease prediction in medicine, crop productivity prediction in agriculture science, market growth prediction in economics, weather forecasting, etc. For all of these reasons, this book provides the most recent developments in AI as well as IC. In this perspective, the book contains the most recent research on machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and other related topics.
List of Contributors
Preface
Acknowledgements
Chapter 1: A New Range Selection Method For Global Best Worst Particle Swarm Optimization
Lalit Kumar, Manish Pandey, and Mitul Kumar Ahirwal
Chapter 2: Automatic Speech Recognition For The Cleft Patients Using Deep Learning Techniques
Srinivasa Reddy K, Brahma Naidu K, Adi Narayana Reddy K, and A. Mallikarjuna Reddy
Chapter 3: Dynamics of Underwater Acoustic Signal Processing: An Underwater Acoustic Marine Habitat Monitoring Application Perspective
Mishachandar B and Vairamuthu S
Chapter 4: Visual Question Answering VGA on Radiology Image - A Survey of Methods And Techniques
Jinesh Melvin YI and Sushopti R. Gawade
Chapter 5: A Comparative Approach For Speech Emotion Recognition Using CNN And Branch CNN
Pratik Kanani, Deepkumar Patel, Sanika Ardekar, Yash Joshi, Nancy Nadar, and Vishakha Shelke
Chapter 6: Revolutionizing Agriculture: A Comprehensive Review of Artificial Intelligence Techniques In Farming
Gautam Siddharth Kashyap, Prerna Kamani, Malvika Kanojia, Samar Wazir, Karan Malik, Vinay Kumar Sehgal, and Rajkumar Dhakar
Chapter 7: Prediction of Vitiligo Skin Disease Spreading Rate by Image Processing
S.Durai, M. Mohamed Iqbal, and M M Venkata Chalapathi
Chapter 8: A Comparative Analysis of Different Approaches to Lexical and Semantic Document Similarity
Pratik Kanani, Devang Shah, Riya Bihani, Khushi Chavan, Aniket Kore, and Nilesh Patil
Chapter 9: Artificial Intelligence In Banking And Financial Services
Naga Simhadri Apparao Polireddi
Chapter 10: Healthcare Applications on Federated Deep Learning For Cyber Security In The Internet of Things
Praneeth Kanagala
Chapter 11: Prediction of Suicidal Risk Using Machine Learning Models
Gautam Siddharth Kashyap, Ayesha Siddiqui, Ramsha Siddiqui, Karan Malik, Samar Wazir, and Alexander E. I. Brownlee
Chapter 12: Information Extraction And Summarization of Medical Reports Using Textract And GPT-2
Pratik Kanani, Tanay Gandhi, Yash Jhaveri, and Varun Mehta
Chapter 13: A Comparative Study on Prediction of Soil Health and Crop Recommendation Using Machine Learning Models
Mithun Shivakoti and Srinivasa Reddy K
Chapter 14: Marine Soundscape Source Separation In The Indian Ocean Region (IOR) Soundscape Using Unsupervised Machine Learning
Mishachandar B, S.P.Abirami, and Arunkumar Balakrishnan
Biography
Dr. Anshul Verma received M.Tech. and Ph.D. degrees in Computer Science & Engineering from ABV-Indian Institute of Information Technology and Management Gwalior, India. He has done Post-doctorate from Indian Institute of Technology Kharagpur, India. Currently, he is serving as Assistant Professor in Department of Computer Science, Institute of Science, Banaras Hindu University Varanasi, India. He has also served as faculty member in Computer Science & Engineering Department at Motilal Nehru National Institute of Technology (MNNIT) Allahabad and National Institute of Technology (NIT) Jamshedpur, India. His research interests include IoT, Mobile ad-hoc networks, Distributed systems, Formal verification, and Mobile computing. He is serving as Editor of the Journal of Scientific Research of the Banaras Hindu University.
Dr. Pradeepika Verma received her Ph.D. degree in Computer Science and Engineering from the Indian Institute of Technology (ISM) Dhanbad, India. She has received M.Tech in Computer Science and Engineering from Banasthali University, Rajasthan, India. Currently, she is working as a Faculty Fellow in Technical Innovation Hub at Indian Institute of Technology, Patna, India. She has worked as a Post-Doctoral Fellow in Department of Computer Science and Engineering at Indian Institute of Technology (BHU), Varanasi, India. She has also worked as an Assistant Professor in the Department of Computer Science and Engineering at Pranveer Singh Institute of Technology, Kanpur, India, and as a Faculty Member in the Department of Computer Application at the Institute of Engineering and Technology, Lucknow, India. Her current research interests include natural language processing, optimization approaches, information retrieval and Mobile ad-hoc networks.
