Machine Learning for Social Transformation

Proceedings of EAIT 2024
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Inhaltsangabe

Credibility Detection Utilizing Fuzzy Weight Strategy.- Image Caption Generation using Neural Networks.- The development of unsupervised Seq2Seq based LSTM Network algorithm for forecasting infectious disease.- Isolated Word Recognition and Feature Extraction Using  Machine Learning.- Bladder Segmentation in MRI for High Dose Rate Brachytherapy Using Deep Network.- Central Bank Digital Currency: Policy Implications through Polarity and Sentiment Analysis.- Advanced Aerial Object Detection using Enhanced YOLOv3 with Leaky ReLU and Dilated Convolutions.- From Field to Cloud: IoT and Machine Learning Innovations in High-Throughput Phenotyping.- Catching Lies in the Act : Early Misinformation Detection using Linguistic Cues and Contextual Information.- DNA Sequencing-induced Cancer Detection: A Representation Learning-inspired Sustainable Transformation in Internet of Healthcare.- Prediction And Analysis of Rare Symptoms Using Association Rule Mining in Health Care Data Without Tree Generation.- Unraveling the Molecular Landscape of Myasthenia Gravis(MG): A Principal Component Analysis (PCA) of  Gene Expression Dataset.- Unlocking the Potential of Machine Learning and Deep Learning for Screening of Geriatric Depression.- IoMT-based Point-of-Care Testing for PCOS Diagnosis using Dempster Shafer Theory of Evidence.- Analysis of Breast cancer classification using deep CNN with adaptive learning rate.- Detecting Schizophrenia Patients Using Deep Learning Models.- Application of Neural Network for Reducing Emission and Optimizing performance of Hydrogen with Biofuel CI Engine.- Water Distribution Network Using IoT Sensors for Residential Areas from Household Rainwater.- A Sustainable, Paperless Environment Using Machine Learning in Hospitals and Medical Sectors.- Deep Feature Learning for Detecting Water Pollution from Industrial Waste.- Multi-Linear Regression Model for Water Prediction and Monitoring in North Twenty-Four Parganas, India.- Machine Learning Based Water Need Estimation for Smart Irrigation System.- Best Defense Practices Against Web Server Attacks By Using and Evaluating NSM Tools.

Produktdetails
  • Erscheinungsdatum: 02.01.2025
  • Autor/Autorin: Jyotsna Kumar Mandal
  • Reihe: Springer Nature Proceedings excluding Computer Science
  • Format: E-Book
  • Dateiformat: PDF
  • Kopierschutz: Wasserzeichen
  • Dateigröße: 24.4 MB
  • Verlag: SPRINGER
  • Sprache: Englisch
  • Umfang: 500 Seiten
  • ISBN: 9789819775323
  • Lieferung: Sofort per Download
  • Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
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