A comprehensive compilation that explores a wide range of applications where deep learning techniques have had impact and its practical uses. The book covers fields like healthcare, finance, autonomous systems, and more. The methodologies such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), and reinforcement learning, have been included.
In healthcare deep learning is used for medical image analysis, disease prediction, and personalized medicine. In the financial sector, aspects like fraud detection, algorithmic trading, and risk management are reviewed. Also autonomous systems, including self-driving cars and drones are explored.
Each chapter includes detailed case studies, experimental results, and insights from leading experts, offering readers both foundational knowledge and advanced techniques. The book serves as a valuable resource for researchers, practitioners, and students seeking to understand the breadth and depth of deep learning applications.
Preface
1. Smart Healthcare Solutions: The Role of Artificial Intelligence in Diagnosing and Treating Patients
2. Artificial Intelligence for Financial Market Forecasting: A Machine Learning Approach
3. Artificial Intelligence for Autonomous Systems: Innovations in Self-Driving Cars and Drones
4. The Integration of Artificial Intelligence and Robotics for Autonomous Systems
5. DD-SSD: Deep Detector for Strip Steel Defects
6. A Prospective study of Indoor Air Quality Monitoring System using IoT
7. Autonomous Plant Monitoring and Maintaining Robot to Identify Plant Diseases and Nutrient Deficiencies
8. Determination and Diagnosis of Diabetes Mellitus
9. Inflated 3D Convnet for Detection of Sign Language
10. Flora and Fauna Identification using YOLOv3 Algorithm
11. Thyroid Cancer Reoccurrence Prediction Using Machine Learning
12. Recommendation System for Social Media Using Graph and Web Analyti
13. Rfid Car Using Arduino Mega 2560 by Dijkstra’s Algorithm
14. Stock Market Analysis Using Ensemble Learning Approach Deep Learning Applications: Select Topics
15. Detecting COVID-19 with Chest X-ray using PyTorch
16. Personalized News Recommendations System Based on Hybrid Filtering Techniques: a case study on user comments and readership history
17. Multilabel Classification of Arabic Articles Based on Mawjaz Topics Using Deep Learning Approaches
18. Data mining in health care sector: A review
19. Translation from Spoken Arabic Digits to Sign Language based on Deep Learning
20. Future Directions in Deep Learning: Challenges and Opportunities
Index
Biography
Laith Abualigah is an Associate Professor at the Computer Science Department at Al Al-Bayt University, Jordan. He is also a distinguished researcher at many prestigious universities. He obtained a PhD from the School of Computer Science at Universiti Sains Malaysia (USM), Malaysia, in 2018. He is Clativate’s Highly Cited Researcher for the years 2021-2024 and a top 1% Influential Researcher, of Web of Science. He is also a top 2% scientist (Stanford University). He has published more than 650 journal papers and books, which collectively have been cited more than 33,000 times (H-index = 81). His main research interests are Artificial Intelligence, Meta-heuristic Modeling, and Optimization Algorithms, Evolutionary Computations, Information Retrieval, Text clustering, Feature Selection, Combinatorial Problems, Optimization, Advanced Machine Learning, Big data, and Natural Language Processing. He is an associate editor of many prestigious journals.
