This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.

Presents the cutting-edge research in deep learning and applications Showcases dynamic synergy between deep learning and computer vision for healthcare industry Includes real world applications in biomedical field

Autorentext

Dr. Uma N. Dulhare is currently working as a Professor & Head Computer Science &Artificial Intelligence Department, MuffaKham Jah College of Engineering & Technology, Hyderabad, India. She has more than 20 years of teaching experience. She received her Ph.D. degree in Computer Science from Osmania University, Hyderabad. Her research interests include Data Mining, Big Data Analytics, and Machine Learning, IoT, Evolutionary Computing, Biomedical Image Processing. She has published more than 40 research papers in prestigious National, International Journals & book chapters. She is a member of the editorial board for various National and International journals in the field of Computer Science and program committee member/reviewer for various International conferences/Journals such as Elsevier, Springer, MDPI, Multimedia Tools & Applications & also chaired the sessions at various International conferences.

Essam H. Houssein (Member, IEEE) received Ph.D. degree in computer science, in 2012. He is currently a Professor of Artificial Intelligence at the Faculty of Computers and Information, Minia University, Minia, Egypt. He is the founder and chair of the Artificial Intelligence Research (AIR) Group, Egypt. He is selected as a Highly Cited Researcher 2023, in 2024 Edition of the Ranking of Top Scientists in the field of Computer Science. He has published more than 240 scientific research articles in prestigious international journals. His research interests include Meta-heuristics Optimization Algorithms, Artificial Intelligence, WSN, Bioinformatics, Internet of Things, Artificial Intelligence, Image Processing, and Data Mining. He serves as a reviewer for more than 120 journals, such as Elsevier, Springer, and IEEE.

Inhalt

Computer-Aided Diagnosis System for Liver Fibrosis Using Data Mining Techniques.- Deep learning for sequence alignment.- Protein Structure Prediction: A Computational Approach to Unravelling Molecular Mysteries.- Management of cancerassociated thrombosis and related complications.- Integrating Machine Vision for Enhanced Biomedical Signal and Image Processing.- Diagnostic strategies using AI and ML in cardiovascular diseases: Challenges and Future Perspectives.- Analytics of medical data using Cognos.- Analytics of Medical Data.- Integrating Deep Learning into Electronic Health Records: Opportunities and Challenges.- Heart disease prediction using machine learning algorithms and quantum variational classifier.- Deep Learning Based Approaches for Early Detection of Parkinson's Disease.- Exploring Recent Developments in Radiographic Chest Disease Detection through Deep Learning Models.- Nano encapsulation for the targeted drug delivery to enhance the efficacy of drugs.- Early Detection of Brain Tumor Automation System using Hybrid SMOTE ENN And Deep Convolution Neural Network Technique.- Advancements in Medical Device Integration Technology and its Impact on Healthcare.- Image Classification To Detect Breast Cancer Using Transfer Learning.- Medical Computer Vision.- Machine Vision & Biomedical Signal and Image Processing.- Metaheuristic Algorithms for Solving Various Optimization Problems: Comprehensive Review.- Maximizing Renewable Energy: Harnessing the Power of Metaheuristic Optimization Techniques.- Review on occurrence of skin lesions due to increased ultra-violet rays for diagnosis of skin cancer to sustain life using deep learning model.- Early Detection of PCOD Automation System using Deep Convolution Neural Network Technique.- Design of Nano Magnetorheological fluid damper - based Leg prosthesis for Amputees.- Learning Analytics in Higher Education: Promises and Challenges.- Neural Network Fusion for Forgery Detection in Digital Images.