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Engineering Applications of Neural Networks: 26th International Conference, EANN 2025, Limassol, Cyprus, June 2629, 2025, Proceedings, Part I [Mīkstie vāki]

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  • Formāts: Paperback / softback, 283 pages, height x width: 235x155 mm, 92 Illustrations, color; 9 Illustrations, black and white; XXXV, 283 p. 101 illus., 92 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2581
  • Izdošanas datums: 22-Jun-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031961951
  • ISBN-13: 9783031961953
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Engineering Applications of Neural Networks: 26th International Conference, EANN 2025, Limassol, Cyprus, June 2629, 2025, Proceedings, Part IPalielināt
  • Formāts: Paperback / softback, 283 pages, height x width: 235x155 mm, 92 Illustrations, color; 9 Illustrations, black and white; XXXV, 283 p. 101 illus., 92 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2581
  • Izdošanas datums: 22-Jun-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031961951
  • ISBN-13: 9783031961953
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031961953.html
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.
.- 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.