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      • Nyhet

      Advances in Smart Computing and Emerging Technologies

      Proceedings of the Third International Conference on Innovative Computing and Cutting-edge Technologies (ICICCT 2025)

      AvKhalid Raza,Basim Alhadidi

      Häftad, Engelska, 2026

      Del 1862 i serien Lecture Notes in Networks and Systems

      2 709 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      This book serves as the official proceedings of the Third International Conference on Intelligent Computing and Cutting-edge Technologies (ICICCT 2025), showcasing a curated collection of ground-breaking research and innovations in the field of intelligent computing. This book is structured into well-defined sections, each addressing key themes of the conference: Foundations of Smart Computing: This book introduces the fundamental concepts, theories, and technologies that form the basis of intelligent computing. Topics include artificial intelligence, machine learning, IoT, and cloud computing. Emerging Technologies in Computing: Delving into state-of-the-art developments, this book covers transformative technologies such as quantum computing, blockchain, 5G, and digital twins, emphasizing their potential to revolutionize industries. Applications of Intelligent Computing: Focused on real-world applications, this book explores how smart systems are being leveraged in healthcare, smart cities, Industry 4.0, and environmental sustainability. Advanced Topics in Computing: Featuring specialized topics such as Explainable AI (XAI), Edge AI, cybersecurity, and human-centric computing, this book provides insights into emerging research areas. Future Trends and Challenges: This forward-looking section identifies promising research directions and discusses the societal and ethical challenges of deploying intelligent systems at scale.

      Produktinformation

      • Utgivningsdatum:2026-08-11
      • Mått:155 x 235 x 29 mm
      • Vikt:791 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Lecture Notes in Networks and Systems
      • Antal sidor:512
      • Förlag:Springer Nature Switzerland AG
      • ISBN:9783032191595

      Utforska kategorier

      • Elektronik och kommunikationer inom Naturvetenskap och teknik
      • Artificiell intelligens inom Data och IT

      Mer om författaren

      Dr. Khalid Raza is an associate professor at the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi, India. Dr. Raza has over 14 years of teaching and research experience at both undergraduate and postgraduate levels. He has contributed over 150 peer-reviewed research articles in refereed international journals, conference proceedings, and book chapters, having a cumulative impact factor of over 300. Dr. Raza has authored/edited 15 books published by reputed publishers like Springer-Nature, Elsevier, and CRC Press. Dr. Raza is an academic editor of PeerJ Computer Science, PLoS ONE and guest editor of npj Precision Oncoloy, JoVE, Natural Product Communications, and Mini-Reviews in Medicinal Chemistry. He has an active collaboration with scientists from leading institutions in India and abroad. He has received grants for Govt. funded research projects.Dr. Basim Alhadidi is presently a full professor at Computer Information Systems Department, Al-Balqa Applied University, Jordan. He earned his Ph.D. in 2000, in Engineering Science (Computers, Systems and Networks). He published many research papers in many topics such as: Computer Networks, Cybersecurity, Image Processing, and Artificial Neural Networks. He is a reviewer for several journals. He was appointed in many conferences as keynote speaker, reviewer, track chair, and track co-chair. His research interest lies in Computer Network, Artificial Intelligence, Image Processing, and Bioinformatics.Dr. Nayyar Ahmed Khan is a long-time software engineer, apple certified trainer, amazon web service educator, and a mentor. He currently works with the Department of Computer Science at College of Computing and Information Technology as an assistant professor at Shaqra University, Riyadh Province of Saudi Arabia. He has a vast teaching experience at the University level. He has published more than 40 papers in reputed journals. He is certified with various industry-level achievements and digital accolades. His experience is enriched by his experience in patents, books, publications, and software deployment. He is a programmer too with an experience in full stack development of software systems.

      Innehållsförteckning

      • A Comprehensive Comparative Study of Traditional Machine Learning and Deep Learning Models for Accurate and Early Lung Cancer Diagnosis.- Enhancing Anomaly Detection in Autonomous Systems Using Deep Learning and Fuzzy Control.- LSTM Neural Networks in Healthcare Disruption Forecasting: A Comprehensive Review and Implementation Framework.- Machine Learning-Based Sentiment Analysis in E-Commerce Text Reviews.- English and Arabic SMS Spam Detection Using Machine Learning.- Night-to-Day Media Conversion Using Generative AI: A CycleGAN-Based Approach with Video Processing.- Learning to Design Interfaces: GUI Generation Using GAN.- Visually-Grounded Textual Reconstruction: An End-to-End System for Assembling Torn Documents and Infilling Content with LLMs.- Novel Contrastive Similarity Learning Approach for Audio-Enabled CLIP Model Using Siamese Network-Based Projections.- A Late Fusion Framework for Multi-Modal Emotion Detection System Using Vision Transformer Models.- A Vision Transformer Framework with Orientational Pooling for Breast Cancer Image Classification.- Edge-Deployed Vision Transformer Model for Automated Keratoconus Classification in Corneal Imaging.- Deep ResNet-Based Classification of Handwritten Devanagari Characters: A Comprehensive Evaluation on DEVA-C-SET Dataset. -An Integrated Deep Learning Approach for Early Detection of Mango Leaf Curl Virus Using YOLOv8 and ResNet50.- Lightweight Deep Learning Model for UAV-Based Disaster Detection.- Similarity Learning–Driven Knowledge Distillation Model for UAV-Based Disaster Events Classification.
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