Computational Intelligence in Engineering Science (eBook, PDF)

First International Conference, ICCIES 2025, Ho Chi Minh City, Vietnam, July 23-25, 2025, Proceedings, Part I
Redaktion: Nguyen, Ngoc Thanh; Tin, Phu Tran; Le Khac, Nhien An; Manolopoulos, Yannis; Hong, Tzung-Pei; Tran, Trong Dao; Pham, van Huy

• Format: PDF

Produktbeschreibung

This four-volume set constitutes the refereed proceedings of the First International Conference on on Computational Intelligence in Engineering Science, ICCIES 2025, in Ho Chi Minh City, Vietnam, during July 23-25, 2025.

The 115 full papers presented in these proceedings were carefully reviewed and selected from 210 submissions. The papers are organized in the following topical sections:

Part I: Machine Learning; Wireless Networks (6G) Part II: Computer Vision; Natural Language Processing Part III: Intelligent Systems; Internet of Things Part IV: Machine Learning; Control Systems

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 430
• Erscheinungstermin: 21. Juli 2025
• Englisch
• ISBN-13: 9783031981616
• Artikelnr.: 74971919

Inhaltsangabe

.- Machine Learning.
.- A Hardware-Friendly Approach for ECG Classification based on Deep Learning Algorithm.
.- PRIMO: A Privacy-Preserving Decentralized Machine Learning Algorithm.
.- Smart Harvesting: Sorting Coffee Fruit Maturity Using Deep Learning.
.- Combining Explainable AI (XAI) and Regression Analysis to Explain Relationships in Electricity Consumption Behavior.
.- Detecting Anomalies and Defects in Integrated Circuits by Ensembling Deep Learning Models.
.- Doctor AI: A Hybrid Model for Clinical Ocular Disease Classification.
.- Forecasting Weather: A Scenario of the Mekong Delta.
.- Melanoma Detection Using Augmented ResNet34 for High-Precision Dermoscopic Image Classification.
.- Abnormal Plum Fruit Detection Using Unsupervised Learning.
.- Hybrid Deep Learning Model for MRI Brain Tumor Identification.
.- Leveraging Machine Learning for Accurate Order Quantity Forecasting: A Case Study of Vietnam s Coffee Production Industry.
.- An Attentive Deep Neuro-Fuzzy Network for Interpretable Breast Cancer Diagnosis.
.- Detection of Littering Behavior Using MobileNet and Vision Transformer.
.- The effectiveness of channel and spatial attention for improving image classification.
.- ATMOS: IoT-Driven Air Quality Monitoring and Forecasting System Using Machine Learning and Fog Computing.
.- Leveraging Deep Neural Networks for Regional Weather Forecasting in Vietnam.
.- Detecting Abnormalities in Chest X-ray Images by Combining Classification Methods, Object Detection, and Data Balancing.
.- Support Decision Making for Supplier Selection using Feature Importance.
.- Optimizing NP-Hard Problems: A Comparative Study of Metaheuristic Algorithms with Benchmark Performance Analysis.
.- Wireless Networks (6G).
.- On the Performance of Downlink LoRa Networks with Fountain Codes and Diversity Techniques.
.- Maximizing Secrecy Performance in UAV-Based Cognitive Relay Systems.
.- Outage Performance of NOMA-Aided Multi-hop Relay Schemes in Underlay Cognitive Networks using Foun-tain Codes.
.- Energy Outage Analysis for NOMA-based UAV-MEC with imperfect CSI and SIC in IoT network.
.- Secure Edge Computing in UAV-Assisted Backscatter Communication NOMA Wireless Sensor Network with Friendly Jamming.
.- Multi-Factor Authentication Healthcare Data Security Framework.
.- Human-Centric Wireless Energy Harvesting System Design for Rural Ubiquitous Communication in Industry 5.0.
.- Performance Analysis of MISO TAS System Using Short Packet Communication Under Impact of Co-Channel Interference.
.- Performance Enhancement for Antenna Array using Partial Ground and Reflective Surface.
.- BLER analysis of Short Packet Communication in Wireless Energy Harvesting Relaying Networks over Nakagami-m fading.
.- A Lightweight Full-Resolution Encoder-Decoder Network for 5G-LTE Spectrogram-based Spectrum Sensing.
.- On Performance Evaluation of Fountain Codes-Based Multicast Scheme in Presence of Multiple Passive Eavesdroppers Over INID Rayleigh Fading Channels.