Enhanced Text Image Analysis for Interdisciplinary Applications
Description
The book serve as a comprehensive guide to researchers, educators and technologists especially in the area of document image analysis for digital humanities. With the help of this ground-breaking book, learn how smartphone text image analysis could revolutionize world. This book examines how digital technology might improve textual artifact discovery, analysis, and interpretation via the perspective of interdisciplinary studies.The books feature practical insights into:Advanced techniques for smartphone text image analysis, innovative approaches to interdisciplinary research in digital humanities, the intersection of technology and textual analysis in diverse fields, case studies and examples showcasing real-world applications, strategies for gaining valuable insights from textual artifacts using digital tools.This book was composed in response to the growing need in interdisciplinary studies within the field of digital humanities for a comprehensive resource that focuses on leveraging digital technologies, particularly smartphone text image analysis techniques, for the exploration, analysis, and acquisition of insights from textual artifacts. Several factors implies the need of developments related to the field of document analysis for digital humanities.1.With the speed at which digital technologies are developing, particularly in the areas of image analysis and natural language processing, it is necessary to investigate the ways in which these technologies can be used to efficiently evaluate text images taken with smartphones.2.Working with scholars, technologists, educators, and policy makers, digital humanities is intrinsically interdisciplinary. This book fosters a bridge between the humanities and technology.3.Textual artifacts are rich sources of information and insights in a variety of fields, including linguistics, literature, history, and cultural studies. The application of advanced analytical methods to textual materials in order to extract relevant knowledge is becoming more and more popular.4.Text image analysis is now easier than ever to do thanks to the growing popularity of smartphones and other digital devices. The goal of this book is to provide professionals, educators, and researchers with useful tools and methods for utilizing widely accessible technologies to analyze text images.5.As digital humanities develop, so do the problems and opportunities for text image analysis. Some of these include handling a variety of languages, historical documents, and intricate textual structures. This book tackles these issues and looks at fresh directions for investigation.
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Persons
N. Shobha Rani is currently an Associate Professor with the Department of Computer Science and Engineering, GITAM School of Technology, GITAM University, Bengaluru. She has more than ten years of experience in the field of precision agriculture, document image analysis, and applications, along with teaching experience of more than 16 years. Her research interests include the field of plant disease detection, crop management using computer vision and deep learning, post-harvest technology development and classification, and other computer vision and deep learning-based technologies for document digitization, OCR, and information capture.
Vinayakumar Ravi (https://vinayakumarr.github.io/) is an Assistant Research Professor at Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia. His previous position was a Postdoctoral research fellow in developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining with Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. His current research interests include applications of data mining, Artificial Intelligence, machine learning (including deep learning) for biomedical informatics, Cyber Security, image processing, and natural language processing. He has more than 100 research publications in reputed IEEE conferences, IEEE Transactions and Journals. His publications include prestigious conferences in the area of Cyber Security, like IEEE S&P and IEEE Infocom. Dr. Ravi has received a full scholarship to attend Machine Learning Summer School (MLSS) 2019, London. He has organized a shared task on detecting malicious domain names (DMD 2018) as part of SSCC'18 and ICACCI'18. He received the Chancellor's Research Excellence Award in AIRA 2021 and his name was included in the World's Top 2% Scientists by Stanford University published in PLoS Biology.
Peeta Basa Pati (Senior Member, IEEE) received the M.Sc. (Eng.) and Ph.D. degrees from the Indian Institute of Science, Bangalore. He is currently a Professor with the Department of CSE, Amrita Vishwa Vidyapeetham, Bengaluru. His research interests include document digitization and information capture. He has close to 25 years of experience in this field which includes more than 15 years of industrial experience. Prior to joining Amrita Vishwa Vidyapeetham, he was with Cognizant Technology Solutions as a Chief Architect. In this role, he has built and managed IDP systems and implemented and successfully productized IDP systems for multiple business domains and organizations. As part of this, he has experience in dealing with documents that are structured and unstructured, typed written and handwritten, dealing with documents with graphical information content. He is also an Alumnus of NIT Rourkela. He has multiple publications and patents to his credit. He has delivered multiple tutorials in the document processing area and has served in the program and technical committees of multiple national and international conferences, besides being a reviewer of papers for conferences and journals.
V. Sowmya received the M.Tech. degree in remote sensing and wireless sensor networks and the Ph.D. degree in artificial intelligence (AI) for natural scene analysis from the Amrita School of Engineering, Coimbatore, Tamil Nadu, India. Since 2011, she has been an Assistant Professor with the Amrita School of Artificial Intelligence, Coimbatore. She is currently an Assistant Professor with the Amrita School of Artificial Intelligence. She has published articles in IEEE TRANSACTIONS, Artificial Intelligence Review, Multimedia Tools and Applications, Neural Computing and Applications, Computers and Security, Healthcare Technology Letters. Her research interests include artificial intelligence for signal and image analysis, biomedical, agriculture, and ecology
Content
Multimodal Hate Speech Detection in South Indian Languages using Attention and Transformers.- Improving Multilingual Speech Emotion Recognition in Tamil and English: From Speaker Dependence to Realistic Multimodal Fusion.- Florence-2 for Medical Visual Question Answering: Using a Cost-Efficient Fine-Tuning Approach.- Remote Sensing Imagery and Parallel Adapters for Flood Based Visual Question Answering.