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Machine Learning and Big Data Analytics: 2nd International Conference on Machine Learning and Big Data Analytics-ICMLBDA, IIT Patna, India, March 2022 de Rajiv Misra

Machine Learning and Big Data Analytics: 2nd International Conference on Machine Learning and Big Data Analytics-ICMLBDA, IIT Patna, India, March 2022: Springer Proceedings in Mathematics & Statistics, cartea 401

Editat de Rajiv Misra, Rana Omer, Muttukrishnan Rajarajan, Bharadwaj Veeravalli, Nishtha Kesswani, Priyanka Mishra
en Limba Engleză Hardback – 7 iun 2023
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence.
The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globeon this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.
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Specificații

ISBN-13: 9783031151743
ISBN-10: 3031151747
Pagini: 566
Ilustrații: X, 566 p. 264 illus., 219 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.98 kg
Ediția:2023
Editura: Springer International Publishing
Colecția Springer
Seria Springer Proceedings in Mathematics & Statistics

Locul publicării:Cham, Switzerland

Cuprins

Preface.- ​A Comprehensive analysis on Mobile Edge Computing: joint offloading and resource allocation perspective.- Finding Significant Project Issues with Machine Learning.- Prediction of Heart Disease using various Data Analysis and Machine learning Techniques.- Artificial Intelligence: Recent Trends, Opportunities and Challenges in Real-World Scenarios.- Bilingual documents text line extraction using Conditional GANs.- Performance Comparison of YOLO Variants for Object Detection in Drone Based Imagery.- A Microservice Architecture with Load Balancing Mechanism in Cloud Environment.- An IoT Application for Detection and Monitoring of Manhole.- Resource Allocation in 5G & Beyond Edge-Slice Networking using Deep Reinforcement Learning.- The Important Influencing Factors in Machine Translation.- Damaged units return Investigation in Printer producing Industry utilizing Big Data.- Colorization of Grayscale Images: An Overview.- Evolutionary Approaches Towards Traditional to Deep Learning Based Chatbot.- Analysis of Machine Learning Algorithms for Detection of Cyber Bullying on Social Networks.- Sentiment Analysis of Political Tweets for Israel using Machine Learning.- A Novel Approach for Real-time Vehicle Re-identification using Content-based Image Retrieval with Relevance Feedback.- Extractive and Abstractive Text Summarization Model fine-tuned based on BERTSUM and Bio-BERT on COVID-19 Open Research Articles.- RevCode for NLP in Indian Languages.- Application for Mood Detection of Students Using TensorFlow and Electron JS.- By Using CNN Technique and Webcam to Identify Face Mask Violation.- A Review on Internet of Things based Cloud Architecture and Its Application.- Prediction of Maneuvering Status for Aerial Vehicles using Supervised Learning Methods.- HRescue: A Modern ML approach for Employee Attrition Prediction.- Using Machine Learning to Detect Botnets in Network Traffic.- Reducing Peak Electricity Demands of a Cluster of Buildings with Multi-agent Reinforcement Learning.- Virus Texture Classification using Genetic Algorithm and Pre-trained Convolutional Neural Networks.- Fog Computing enabled Internet of Things for resource optimization.- Network Media Content Model in the era of Smaft Devices.- Sentimental Analysis of Stock Market via Twitter.- Detection and Classification of Tumor Tissues in Colorectal Cancer using Pathology Images.- Challenges encountered in the implementation of machine learning in the healthcare industry.- Performance Evaluation of Deep Learning Architectures for Recognition of Moisture in Dried Coconut Copra.- Training Generative Adversarial Networks(GANs) over Parameter Server and Worker Node Architecture.- Handwritten Digit Recognition using Neural Network with Gabor Filter for Information Fusion.- FAFOC: Fog Based Energy Efficient Clustering Technique for Wireless Sensor Networks.- Evaluation of Supervised Classifiers for Fake News Detection using Twitter Dataset.- Analysis of Pest Recognition using Lightweight CNN.- Early Prediction of Alzheimer Disease Using Ensemble Learning Models.- Cattle Identification from Muzzle Print Image Pattern Using Hybrid Feature Descriptors and SVM.- Evaluate and Detection of Breast Cancer using Data Mining Models.- Lung Cancer Disease Prediction Using Machine Learning Techniques.- Video to Text Generation Using Sentence Vector and Skip Connections.- Machine Learning Techniques for COVID-19 pandemic updates for Analysis, Visualization and Prediction system.- Design and CFD Analysis of Drone Thrust with Duct.- Index.











Textul de pe ultima copertă

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence.
The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.

Caracteristici

Includes cutting-edge research from around the globe Discusses current status, trends, future directions, and opportunities Written for beginners, young researchers, and academics