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Engineering Applications of Neural Networks
Details
The two-volume set CCIS 2581 and 2582 constitutes the refereed proceedings of the 26th International Conference on Engineering Applications of Neural Networks, EANN 2025, held in Limassol, Cyprus during June 2629, 2025.
The 41 full papers included in these proceedings were carefully reviewed and selected from 101 submissions. These papers demonstrate the vitality of Artificial Intelligence algorithms and approaches, as well as AI applications.
Klappentext
.- A Real-Time Human Action Recognition Model for Assisted Living. .- A Survey of Federated Learning-Based Intrusion Detection Methods in Medical IoT .- AI-based automatic counting and classification of aedes mosquito eggs in field traps. .- An Empirical Review of Uncertainty Estimation for Quality Control in CAD Model Segmentation. .- Brain Inspired Learning for Neural Networks. .- Comparative Analysis of Machine Learning Techniques for Chronic Kidney Disease Prediction Efficiency. .- Detecting Anomalous Self-Citations using Citation Network Analysis and LLMs. .- Early Detection of Voice Pathology from Cry Analysis Using Non-Interpretable Features and Parallel 1D CNN. .- Easy, Fast and Reliable Modulo and Linear Congruential Generator Approximation with Artificial Neural Networks. .- EEG-based Hybrid Emotion Recognition Model with Statistical-Wavelet Features and Modality-Agnostic Loss. .- ESN with delayed inputs to model industrial processes. .- Exploring Knowledge Distillation for Model Compression in Edge Environments. .- Exploring Various Sequential Learning Methods for Deformation History Modeling. .- FusionNet:Leveraging Dual Speech Separation Networks for Enhanced Multi-Speaker Isolation. .- Hybrid Deep Learning and Gradient Boosting for Superior Sentiment Analysis: A Comparative Study. .- Implementing Hybrid Tsetlin Machine and Q-Learning for Solving the Job Shop Scheduling. .- Maximum Interstory Drift Ratio (MIDR) equations for R/C buildings using machine learning procedures. .- MRI-Based Brain Tumor Classification Using Ensemble CNN, VGG16, and ResNet50 Model. .- Needle-in-the-Haystack Testing LLMs with a Complex Reasoning Task. .- Utilizing Multiple Data Sources to Improve Prediction of Severe Weather Events through Spatio-Temporal Analysis.
Inhalt
.- A Real-Time Human Action Recognition Model for Assisted Living.
.- A Survey of Federated Learning-Based Intrusion Detection Methods in Medical IoT
.- AI-based automatic counting and classification of aedes mosquito eggs in field traps.
.- An Empirical Review of Uncertainty Estimation for Quality Control in CAD Model Segmentation.
.- Brain Inspired Learning for Neural Networks.
.- Comparative Analysis of Machine Learning Techniques for Chronic Kidney Disease Prediction Efficiency.
.- Detecting Anomalous Self-Citations using Citation Network Analysis and LLMs.
.- Early Detection of Voice Pathology from Cry Analysis Using Non-Interpretable Features and Parallel 1D CNN.
.- Easy, Fast and Reliable Modulo and Linear Congruential Generator Approximation with Artificial Neural Networks.
.- EEG-based Hybrid Emotion Recognition Model with Statistical-Wavelet Features and Modality-Agnostic Loss.
.- ESN with delayed inputs to model industrial processes.
.- Exploring Knowledge Distillation for Model Compression in Edge Environments.
.- Exploring Various Sequential Learning Methods for Deformation History Modeling.
.- FusionNet:Leveraging Dual Speech Separation Networks for Enhanced Multi-Speaker Isolation.
.- Hybrid Deep Learning and Gradient Boosting for Superior Sentiment Analysis: A Comparative Study.
.- Implementing Hybrid Tsetlin Machine and Q-Learning for Solving the Job Shop Scheduling.
.- Maximum Interstory Drift Ratio (MIDR) equations for R/C buildings using machine learning procedures.
.- MRI-Based Brain Tumor Classification Using Ensemble CNN, VGG16, and ResNet50 Model.
.- Needle-in-the-Haystack Testing LLMs with a Complex Reasoning Task.
.- Utilizing Multiple Data Sources to Improve Prediction of Severe Weather Events through Spatio-Temporal Analysis.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031961953
- Genre Information Technology
- Editor Lazaros Iliadis, Ilias Maglogiannis, Efthyvoulos Kyriacou, Chrisina Jayne
- Lesemotiv Verstehen
- Anzahl Seiten 283
- Größe H17mm x B155mm x T235mm
- Jahr 2025
- EAN 9783031961953
- Format Kartonierter Einband
- ISBN 978-3-031-96195-3
- Titel Engineering Applications of Neural Networks
- Untertitel 26th International Conference, EANN 2025, Limassol, Cyprus, June 26-29, 2025, Proceedings, Part I
- Gewicht 488g
- Herausgeber Springer
- Sprache Englisch