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      Proceedings of 4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications

      ICMISC 2023

      AvVinit Kumar Gunjan,Jacek M. Zurada

      Häftad, Engelska, 2024

      Del 873 i serien Lecture Notes in Networks and Systems

      2 394 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      The book is a collection of the best-selected research papers presented at the International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications (ICMISC 2023) held in September 2023 at the CMR Institute of Technology, Hyderabad, Telangana, India. This book will contain articles on current trends in machine learning, the internet of things, and smart city applications, emphasizing multi-disciplinary research in the area of artificial intelligence and cyberphysical systems. The book is a great resource for scientists, research scholars, and PG students to formulate their research ideas and find future directions in these areas. Further, this book serves as a reference work to understand the latest technologies used by practice engineers across the globe.

      Produktinformation

      • Utgivningsdatum:2024-05-23
      • Mått:155 x 235 x 42 mm
      • Vikt:1 386 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Lecture Notes in Networks and Systems
      • Antal sidor:814
      • Förlag:Springer Verlag, Singapore
      • ISBN:9789819994410

      Utforska kategorier

      • Elektronik och kommunikationer inom Naturvetenskap och teknik
      • Systemvetenskap och AI inom Data och IT
      • Regional planering inom Naturvetenskap och teknik

      Mer om författaren

      Vinit Kumar Gunjan is Associate Professor in the Department of Computer Science & Engineering and Dean of Academics at CMR Institute of Technology Hyderabad (affiliated with Jawaharlal Nehru Technological University, Hyderabad).  An active researcher, he has published research papers at IEEE, Elsevier, and Springer conferences, authored several books, and edited volumes of Springer series. Awarded the prestigious Early Career Research Award in 2016 by the Science Engineering Research Board, Department of Science and Technology, Government of India He is a senior member of IEEE, Additional Treasurer, chair of the IEEE Computer Society chapter Hyderabad, and an active volunteer in the IEEE Hyderabad section. He volunteered in the capacities of Treasurer, Secretary, and Chairman of CIS, IEEE Young Professionals Affinity Group, & IEEE Computer Society. He was involved as organizer in many technical & non-technical workshops, seminars, and conferences of IEEEand Springer. He had the privilege of working with the top IEEE executives during his tenure, and the IEEE Hyderabad Section awarded him the Best IEEE Young Professional Award in 2017.Jacek M. Zurada (SM’85, F’96, LF’14) is Professor of Electrical and Computer Engineering and Director of the Computational Intelligence Laboratory at the University of Louisville, Louisville, Kentucky, USA, where he served as Department Chair and a Distinguished University Scholar. He was Professor at Princeton University, Northeastern University, Auburn University, the National University of Singapore, Nanyang Technological University in Singapore, Chinese University of Hong Kong, the University of Chile, Santiago, Toyohashi University of Technology, Japan, the University of Stellenbosch, South Africa, the University of Marie-Curie, Paris, France, and was Postdoctoral Fellow at the Swiss Federal Institute of Technology, Zurich, Switzerland.

      Innehållsförteckning

      • Defect Detection in Metal Surfaces using Computer Vision.- Liver Cirrhosis Prediction using Machine Learning Classification Techniques.- A Recent Survey on Risk Factors Affecting the Blood Pressure in India.- Rock Segmentation of Real Martian Scenes using Dual Attention Mechanism-Based U-Net.- An Efficient approach of True Random Number Generation using A Data encryption method in Security & cryptography algorithm.- Background Subtraction for Detecting Moving Objects and Implementing On FPGA Board.- Crime Pattern Identification and Prediction using Machine Learning.- Rash Driving Detection And Alerting System.- Logistic based OVA-CNN Model for Alzheimer's Disease Detection and Prediction using MR Images.- 3D Avatar Reconstruction using Multi-Level Pixel-Aligned Implicit Function.- Text-to-Image Generation Model with DNN Architecture and Computer Vision for Embedded Devices using Quantization Technique.- One Shot Learning for Archaeological Site Data Using Deep Neural Network on Embedded Systems.- Indian Music Instrument Classification using Deep Learning on Embedded Platforms.- Innovative Design of a Solar-Powered Wireless Soil Moisture Sensor for Maximizing the Efficiency of IoT based Systems.- Image Inpainting on Archeological Dataset using UNet Architecture on Embedded Platform.- A Deep Learning Model-Based Approach for Brain Tumor Detection in Low Brightness and Low Contrast MRI.- Implementation of IoT and Data analytics in smart agricultural system.- Implementing Service-Oriented game-theoretic Security Scheme for IoV Networks in Self-Driving Cars.- Framework for 2D MRI Brain Tumour Segmentation Employing Znet-Based Deep Learning.- Multiple-Emotion Recognition in Gujarati Language using Natural Language Processing.- Automation of Mechanical Ventilation for Optimal Pressure Predictions using Machine Learning.- Rhythm Net: A Novel Convolution Neural Network for Multi-Class ECG Classification.- Designing of GUI based Home Automation System using Arduino and MATLAB.- Recent Trends of Information Retrieval System: Review based on IR models and applications.- Capsule Network Approach for Image Classification.- Empowering Fast-Moving Consumer Goods Supply Chain Leveraging Blockchain.- DeEffNet: A CNN model for optimizing the Image Classification of Comorbid Patients.- A Comparative Study of Approaches to Short Text Document Clustering.- Secure Image Retrieval in an Untrusted Cloud Environment.- Automated Pest Detection using Image Classification.
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