Smart Objects and Technologies for Social Good by Huynh, Hiep Xuan; Pham, Congduc; Duong-Trung, Nghia;

Hosszú leírás:

The two-volume set LNICST 648 and 649 constitutes the refereed post-conference proceedings of the 10th EAI International Conference on Smart Objects and Technologies for Social Goods, GOODTECHS 2024, held in Can Tho, Vietnam, during December 19–20, 2024.

The 17 full papers and 27 short papers included in these volumes were carefully reviewed and selected from 102 submissions. They focus on a wide range of advancements in smart technologies aimed at promoting social good. Key topics include cutting-edge research in Internet of Things (IoT) security, innovative applications of artificial intelligence in domains such as healthcare, education, and environmental monitoring, and energy-efficient systems. They were organized in topical sections as follows:

Part I: Advances in Artificial Intelligence, Machine Learning, and Blockchain Applications Across Diverse Domains

Part II: Innovations in Energy-Based Models, and Advanced Predictive Systems Across Diverse Domains

Tartalomjegyzék:

Part-volume-I:

Advances in Artificial Intelligence, Machine Learning, and Blockchain Applications Across Diverse Domains.

.- A Comparison of Deep Learning Models for White Blood Cell Detection.

.- An Integration of VGG19 and SARIMAX in Water Level Forecasting Using Satellite Imagery and Time Series Data.
.- Using Auto Immune LightGBM (AI-LGBM) for Prediction of Ground Water Quality in Vietnam and Indian Regions.
.- EIS-PoI: An Energy-driven Approach for Instance Segmentation Using Points of Interest.
.- Blockchain Application in Online Certificate Issuance and Verification Certificate System.
.- Smart Contract Integration in Tuition Management.
.- Model Integrating CNN, Gated Recurrent Unit and Genetic Algorithm for Rainfall Forecasting from Radar Images at Phadin Station.
.- Approach to Scalable Machine Learning Operations (MLOps) Architectures for Research Labs with Limited Hardware Resources.
.- A New Architecture for Controlling IoT Devices of Smart Room using ESP32 Microcontroller.
.- Energy Correlation-Based EBM for Skin Lesion Classification: A Novel Approach.
.- Caught in the Lens: Zero-Shot BioCLIP Struggles with Camera Trap Wildlife Images.
.- Blending Federated Learning and Value-Sensitive Design for Ethics and Privacy-Preserving in Education
.- Missing Data Imputation for Sensor Observation Streams Leveraging Data Correlation and Message Propagation
.- Analyzing Social Networks Using Graph Neural Networks with Advanced Hyperparameter Optimization Techniques
.- Automatic Recognition and Scoring System in Military Training Applies Modern Deep Learning Techniques
.- Enhancing Transformer-Based Object Detection Model For Aerial Images
.- Water Quality Inspection System for Mariners Using EKI’s Continuous Learning Algorithms.

Part-volume-II:
Innovations in Energy-Based Models, and Advanced Predictive Systems Across Diverse Domains.

.- Enhancing the Quality of Recommendation Lists using Graph Convolutional Networks.
.- A Method Utilizing Energy Distance to Address Sparsity of Dataset in Recommendation Systems.
.- Energy-Based Models with Energy Distance for Video Captioning.
.- Detecting Driver Drowsiness Using Deep Learning Techniques.
.- Energy Distance in Popular Filtering and Recommendation.
.- Enhancing User-Base Context-Aware Collaborative Filtering Using Energy Distance with Pre-Filtering Contextual Features.
.- Enhancing Motion Estimation with BM-EDM Method.
.- EMPD: Energy-based Motion Pattern Detection.
.- Personalized Travel Experiences: Contextual Data-Based Recommendation Solutions.
.- Enhancing Deep Learning Models for Crop Disease Detection Using Keras Tuner.
.- Missing Data Imputation with Graph Neuron Networks and Message Propagation.
.- A novel framework for real-time analysis of outlier IoT data.
.- Cortex Vision: Detection of Ophthalmic Disease Using Machine Learning Algorithm.
.- Real-time Object Detection Based on Yolov8.
.- Combining Accuracy and Diversity to Enhance the Quality of the Recommender System.
.- Combining Lightweight Deep Learning Models with Data Augmentation for Analysis of Cervical Cells.
.- Energy-based Framework for Tag-based Recommendation Systems.
.- Enhancing Water level forecasting models Based on Ensemble Learning.
.- Advanced Predictive Modeling of Forex Market Fluctuations Using Ensembles Learning.
.- Data Analysis and Classification of the News.
.- Building An Automatic Traffic Monitoring System Based On Webgis 3D.
.- Detecting Abnormal Cervical Cells Based on Segmentation of Overlapping Cells.
.- A Multi-model Testcase Recommendation System for Teaching Programming in Higher Education.
.- Energy-Based Bounding Box Generation for Object Detection.
.- Forecasting Storms and Floods in Vietnam with Deep Learning Methods.
.- Lane-based vehicle recognition using deep learning models.
.- Application of Machine Learning Models for Cardiovascular Disease Prediction.