Applications of Artificial Intelligence and Data Science: First Global Conference, AAIDS 2024, London, UK, April 3–5, 2024, Proceedings

Author:   Mufti Mahmud ,  Nelishia Pillay ,  M Shamim Kaiser
Publisher:   Springer International Publishing AG
Volume:   2601
ISBN:  

9783031984976


Pages:   418
Publication Date:   02 October 2025
Format:   Paperback
Availability:   Not yet available   Availability explained
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Applications of Artificial Intelligence and Data Science: First Global Conference, AAIDS 2024, London, UK, April 3–5, 2024, Proceedings


Overview

This CCIS post conference volume constitutes the proceedings of First Global Conference on Applications of Artificial Intelligence and Data Science, AAIDS 2024,  in London, UK, April 2024.  The 30 full papers presented were carefully reviewed and selected from 147 submissions. They were focused on topical sections as follows: Advanced Computing and Statistics; Data Science and Hybrid AI Systems.

Full Product Details

Author:   Mufti Mahmud ,  Nelishia Pillay ,  M Shamim Kaiser
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Volume:   2601
ISBN:  

9783031984976


ISBN 10:   3031984978
Pages:   418
Publication Date:   02 October 2025
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

.- Advanced Computing and Statistics .- Towards Reserve Margin Correction via Outage Capacity Forecasting Using Gramian Angular Field and Long Short-Term Memory (LSTM). .- Comparison of Hyperspectral Image Reconstruction for Medical Images. .- Kidney MRI Segmentation Using Deep Learning. .- A Comparative Analysis of Ensemble Strategies for Enhanced Machine Learning Results. .- Neural Network -Based Robust Adaptive OutputFeedback Control for MIMO Time-Varying Delay Systems. .- Potato Leaf Disease Classification Using Resnet50ViT. .- Indonesian Named Entity Recognition Model for Identifying Human Hobbies. .- Comparative Analysis Between Time Series Feature Extraction with Sliding Window and Data Framing Method for Energy Forecasting Using Artificial Neural Network. .- An Internet of Drone Things-Enabled Inspection Ecosystem for Smart Cities and Society. .- Enhancing Wireless Sensor Network Security Against Wormhole Attacks with Twofish Encryption. .-  Data Science .- Classifying Depressed and Healthy Individuals Using Wearable Sensor Data: A Comparative Analysis of Machine Learning and Deep Learning Approaches. .- Detour: Understanding the Application of Artificial Intelligence Based Models in Forecasting Safe Travel Routes. .- An Approach to Compute the Adaptive Dynamic Diameter of Data Stream Clusters. .- XMR Net: A Deep Model for Vehicle Make and Model Recognition Using Still-Images. .- Semi-Automatic Tool to Assist Radiologist for Pneumothorax Detection and Localization. .- Parenthood Responsibility Mining Using Social Network Mining Approach. .- Unleashing Machine Learning for Accurate Weather Forecasts. .- BFL: Blockchain-Federated Learning for Privacy Preservation in Internet of Underwater Things. .- Exploring and Contrasting Machine Learning Classifiers for Citrus Plant Disease Classification. .- GloVe-LSTM: An Artificial Attention-Based Algorithm for Sentiment Analysis of Pandemic Times for Enhanced Decision Support. .- Hybrid AI Systems .- .Breast DCE-MRI Registration Using Student Psychology-based Optimization Algorithm with Centroid Opposition-Based Learning .- Brain MRI Registration Using Fireworks Algorithm. .- Quantifying Climate Change Effects on Standard Minimum and Maximum Average Temperature Extremes in Bangladesh: A Machine Learning Regression Analysis from past to Present. .- Explainable Machine Learning Strategy to Discover Attributes Accountable for ASD Detection. .- Short-Term Water Demand Forecasting: A Comparative Study of Deep Learning and Conventional Machine Learning Algorithms. .- Improving Crop Yield Prediction Accuracy: A Hybrid Machine Learning Approach. .- PPIoDT: GSO-FL Based Privacy Preserving IoDT Guided Ocean-Wind Aware Ship Trajectory Recommendation. .- Multiple Linear Regression based Multipath Green Routing for Internet of Vehicular Things in Smart Cities. .- FemCrop: A Femtocell-Based Edge-Cloud Frame-Work for Crop Yield Prediction Using Deep Learning. .- Detection of ransomware attacks using federated learning based on the CNN model.

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