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[null,"1.","Record Nr.",null,"UNISA996691663403316"]
[null,null,"Autore",null,"Rojas Ignacio"]
[null,null,"Titolo",null,"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"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026"]
[null,null,"ISBN",null,"3-032-02725-X"]
[null,null,"Edizione",null,"[1st ed. 2026.]"]
[null,null,"Descrizione fisica",null,"1 online resource (1009 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 16008"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- Advanced Topics in Computational Intelligence.  -- Power Quality 24-hour Prediction Based on L-Transform Derivative Modular and Deep Learning Statistics Using Environmental Data in detached Smart Buildings.  -- Incremental Feature Learning of Shallow Feedforward Regression Neural Networks using Particle Swarm Optimisation.  -- Resilience Under Attack: Benchmarking Optimizers Against Poisoning in Federated Learning for Image Classification Using CNN.  -- VIDEM: VIDeo Effectiveness and Memorability Dataset.  -- Penetration Testing with AI: Case Studies on LLM and RL-Based Attack Agents.  -- A comparative study of deep learning approaches for classifying wild and cultivated fish.  -- Sparse Least Square SVM in Primal via Nesterov Accelerated Alternating Directions Method of Multipliers.  -- AI:Bioinformatics and Biomedical Applications.  -- A transformer-based model to predict micro RNA interactions.  -- Leveraging Large Language Models on Assay Descriptions to Improve the Prediction of Inhibitors for Mycobacterium tuberculosis.  -- Advancing Imminent Fracture Risk Prediction: Integrating Machine Learning with Enhanced Feature Engineering.  -- Self-organizing Maps for Missing Value Imputation in Transcriptomic Datasets.  -- ANN HW-Accelerators.  -- RECS: A Scalable Platform for Heterogeneous AI Acceleration in the Cloud-Edge Continuum.  -- Evaluating HBM to accelerate neural networks on FPGAs demonstrated using binary neural associative memories.  -- Resource-efficient Implementation of Convolutional Neural Networks on FPGAs with STANN.  -- High-Performance FPGA-"]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","The two-volume set LNCS 16008 & 16009 constitutes the refereed 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 "]
[{"$nulls":4},"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."]