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Record Nr. |
UNISA996691663403316 |
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Autore |
Rojas Ignacio |
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Titolo |
Advances in Computational Intelligence : 18th International Work-Conference on Artificial Neural Networks, IWANN 2025, A Coruña, Spain, June 16–18, 2025, Proceedings, Part I / / edited by Ignacio Rojas, Gonzalo Joya, Andreu Catala |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
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ISBN |
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Edizione |
[1st ed. 2026.] |
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Descrizione fisica |
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1 online resource (1009 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 16008 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- Advanced Topics in Computational Intelligence. -- Power Quality 24-hour Prediction Based on L-Transform Derivative Modular and Deep Learning Statistics Using Environmental Data in detached Smart Buildings. -- Incremental Feature Learning of Shallow Feedforward Regression Neural Networks using Particle Swarm Optimisation. -- Resilience Under Attack: Benchmarking Optimizers Against Poisoning in Federated Learning for Image Classification Using CNN. -- VIDEM: VIDeo Effectiveness and Memorability Dataset. -- Penetration Testing with AI: Case Studies on LLM and RL-Based Attack Agents. -- A comparative study of deep learning approaches for classifying wild and cultivated fish. -- Sparse Least Square SVM in Primal via Nesterov Accelerated Alternating Directions Method of Multipliers. -- AI:Bioinformatics and Biomedical Applications. -- A transformer-based model to predict micro RNA interactions. -- Leveraging Large Language Models on Assay Descriptions to Improve the Prediction of Inhibitors for Mycobacterium tuberculosis. -- Advancing Imminent Fracture Risk Prediction: Integrating Machine Learning with Enhanced Feature Engineering. -- Self-organizing Maps for Missing Value Imputation in Transcriptomic Datasets. -- ANN HW-Accelerators. -- RECS: A Scalable Platform for Heterogeneous AI Acceleration in the |
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Cloud-Edge Continuum. -- Evaluating HBM to accelerate neural networks on FPGAs demonstrated using binary neural associative memories. -- Resource-efficient Implementation of Convolutional Neural Networks on FPGAs with STANN. -- High-Performance FPGA-based CNN Acceleration for Real-Time DC Arc Fault Detection. -- Optimizing AI on the Edge: Partitioning Neural Networks Across Heterogeneous Accelerators. -- Comparison of Hardware Component and Manycore Implementation for Anomaly Detection in Trustworthy System-on-Chips. -- Bio-Inspired Systems and Neuro-Engineering. -- An Emotional Classifier for Machine’s Artificial Visual Aesthetic Appraisal. -- Hardware and Software influence on EAs power consumption. -- Properties of monoclinic gallium oxide film and its photomemristor application in nonlinear RMC circuit. -- A perceptron-like neural network implementing a learning-capable K-nearest neighbor classifier. -- From Biological Neurons to Artificial Neural Networks: A Bioinspired Training Alternative. -- Recent Advances in Deep Learning. -- Domain Adaptation of the Whisper ASR Model for Tourism Call Center Transcription in Polish. -- Learning to Search with Subgoals. -- Towards Speaker Independent Speech Emotion Recognition by means of Dataset Aggregation. -- Learning Heuristics for k-NANN-A*: A Deep Learning Approach. -- Evaluating Higher-Level and Symbolic Features in Deep Learning on Time Series: Towards Simpler Explainability. -- Energy-Efficient Radio Resource Allocation in 5G Using Deep Q-Networks. -- Multi-view Cross Contrastive Learning for Multimodal Knowledge Graph Recommendation. -- MuleTrack: A Lightweight Temporal Learning Framework for Money Mule Detection in Digital Payments. -- Modular Deep Neural Networks with residual connections for predicting the pathogenicity of genetic variants in non coding genomic regions. -- Modeling Student–Subject Interactions with GNNs for Grade Prediction. -- Deploying Vision Foundation AI Models on the Edge. The SAM2 Experience. -- Generative AI for Contextualizing Bronze Age Objects in Historical Scenes. -- G-TED SAM: Node Classification via Graph Transformer to Simple Attention Model Distillation. -- Expression Recognition in Faces Partially Occluded by Head-Mounted Displays. -- Reinforcement Learning for Mapless Navigation: Enhancing Exploration with Image-Based Rewards. -- Deep Learning Applied to Computer Vision, Healthcare and Robotics. -- Human Activity Recognition in the Classroom using Low-cost Sensors. -- Hybrid dropout for deep ordinal classification. -- Enhanced video-based eye status detection in term infants. -- Knee osteoarthritis severity grading using soft labelling and ordinal classification. -- Self-attentive bidirectional LSTM networks for temporal decoding of EEG motor states. -- Effects of Grouped Structural Global Pruning of Vision Transformers on Domain Generalisation. -- MORENA: Empty images detection based on unsupervised reconstruction error analysis. -- Methodological framework for the creation of digital twins for photovoltaic power plants. -- Decoding Brain Lobe Contributions in EEG for automatic detection of obstructive sleep apnea. -- Emerging Methodologies in Time Series Forecasting. -- Forecasting Non-Stationary Time Series: A Comparison of Deep and Shallow Neural Network Architectures. -- Deep Learning or Trees? A Trade-off Analysis for Multivariate Time Series Forecasting. -- Hybrid AI Models for Structured Mobility Prediction in Metropolitan Areas. -- XAI for univariate and multivariate time series forecasting. A case study on electricity consumption in Romania’s National Electricity Network. -- Assessing bias in the evaluation of blood glucose prediction models. |
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Sommario/riassunto |
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The two-volume set LNCS 16008 & 16009 constitutes the refereed |
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conference proceedings of the 18th International Work-Conference on Advances in Computational Intelligence, IWANN 2025, held in A Coruña, Spain, during June 16–18, 2025. The 103 revised full papers presented in these proceedings were carefully reviewed and selected from 144 submissions. The papers are organized in the following topical sections: Part I: Advanced Topics in Computational Intelligence; AI:Bioinformatics and Biomedical Applications; ANN HW-Accelerators; Bio-Inspired Systems and Neuro-Engineering; Recent Advances in Deep Learning; Deep Learning Applied to Computer Vision, Healthcare and Robotics; and Emerging Methodologies in Time Series Forecasting. Part II: Explainable and Interpretable Machine Learning (xAI) with a Focus on Applications; General Applications of AI; ITOMAD – Intelligent Techniques for Optimization, Modeling, and Anomaly Detection; Machine Learning for 4.0 Industry Solutions; Machine Learning for Photovoltaic System Optimization and Control in Modern Energy Grids; New and future advances in BCI-based Spellers; and Social and Ethical aspects of AI. |
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