Nibaran Das - Böcker

Deep Learning Models for Medical Imaging explains the concepts of Deep Learning (DL) and its importance in medical imaging and/or healthcare using two different case studies: a) cytology image analysis and b) coronavirus (COVID-19) prediction, screening, and decision-making, using publicly available datasets in their respective experiments. Of many DL models, custom Convolutional Neural Network (CNN), ResNet, InceptionNet and DenseNet are used. The results follow 'with' and 'without' transfer learning (including different optimization solutions), in addition to the use of data augmentation and ensemble networks. DL models for medical imaging are suitable for a wide range of readers starting from early career research scholars, professors/scientists to industrialists. Provides a step-by-step approach to develop deep learning models Presents case studies showing end-to-end implementation (source codes: available upon request)

Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text.In brief, the book offers comprehensive coverage of the most essential topics, including:· The role of AI for document image analysis· Optical character recognition· Machine learning algorithms for document analysis· Extreme learning machines and their applications· Mathematical foundation for Web text document analysis· Social media data analysis· Modalities for document dataset generationThis book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.

This book features high-quality, peer-reviewed research papers presented at the International Conference on Data Electronics and Computing (ICDEC 2023) organized by Department of Computer Science & Engineering, Mizoram University (A Central University) Aizawl, India & Department of Computer Science & Engineering, National Institute of Technology Mizoram Aizawl, India during 15 – 16 December 2023. The book covers topics in communication, networking and security, image, video and signal processing; cloud computing, IoT and smart city, AI/ML, big data and data mining, VLSI design, antenna, and microwave andcontrol.

This book features high-quality, peer-reviewed research papers presented at the International Conference on Data Electronics and Computing (ICDEC 2023) organized by Department of Computer Science & Engineering, Mizoram University (A Central University) Aizawl, India & Department of Computer Science & Engineering, National Institute of Technology Mizoram Aizawl, India during 15 – 16 December 2023. The book covers topics in communication, networking and security, image, video and signal processing; cloud computing, IoT and smart city, AI/ML, big data and data mining, VLSI design, antenna, and microwave and control.

This book features high-quality, peer-reviewed research papers presented at the International Conference on Data Electronics and Computing (ICDEC 2022) organized by departments of Electronics and Communication Engineering, Computer Applications, and Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India during 7 – 9 September, 2022. The book covers topics in communication, networking and security, image, video and signal processing; cloud computing, IoT and smart city, AI/ML, big data and data mining, VLSI design, antenna, and microwave and control.