Neural Information Processing : 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2–6, 2024, Proceedings, Part XV / / edited by Mufti Mahmud, Maryam Doborjeh, Kevin Wong, Andrew Chi Sing Leung, Zohreh Doborjeh, M. Tanveer

• Autore: Mahmud Mufti
• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025
• Edizione: 1st ed. 2025.
• Descrizione fisica: 1 online resource (639 pages)
• Disciplina: 006.4
• Soggetto topico: Pattern recognition systems; Data mining; Machine learning; Social sciences - Data processing; Automated Pattern Recognition; Data Mining and Knowledge Discovery; Machine Learning; Computer Application in Social and Behavioral Sciences
• Altri autori: DoborjehMaryam HuangDejiang LeungAndrew Chi Sing DoborjehZohreh TanveerM
• Nota di contenuto: Utilizing Deep Learning to address Temporal and Spatial Dependencies in Weather Forecasting -- Imagined Digits Recognition Based on Masked Electroencephalography Modeling -- THGCN:Temporal Hypergraph Convolutional Network for Subject Independent EEG Emotion Recognition -- ANN-Based Pollution Forecasting Through Short-Term Spatio-Temporal Analysis: A North Island, New Zealand Case Study -- Detection of Animal Movement from Weather Radar using Self-Supervised Learning -- From Concrete to Abstract: A Multimodal Generative Approach to Abstract Concept Learning -- Analysis on Artificial Representations of a Trained AlexNet Model Using the CIFAR-10 Dataset -- Modelling the influence of temperature and rainfall on the spread of African swine fever in Australia -- An EEG-based Spatial-Temporal Hybrid Architecture for Cognitive Load Detection -- Decoding Psychological Stress during Laparoscopic Surgery Training: Insights from EEG -- A Comparison between baseline models and a transformer network for SOC prediction of lithium-ion batteries -- Insights into Long-term Electrical Load Forecasting: Explainable AI approach on Multivariate LSTM -- Artificial Intelligence and Climate Change: A Review of Causes and Opportunities -- Towards a machine learning model to predict cognitive ability using EEG data and virtual spatial navigation task scores in intellectually disabled adults -- HyPeFL: Tackling Data Heterogeneity via Hypernetwork in Personalized Federated Learning -- NeuroGeMS: An open-source GUI software for multimodal modelling in biomedical research and applications -- Multimodal Multiview Graph Convolution Network for the Diagnosis of Alzheimer’s Disease -- DNA-PRIME: Advanced DNA Sequence Compression through Enhanced Feature Fusion and Weight Hashing -- SnE-VNet: A Deep Learning Model with Squeeze and Excitation for Improved 3D Stroke Lesion Segmentation -- Morphology-Guided 3D Skull Gender Identification with Point-BERT -- Cuffless Blood Pressure Measurement From Photoplethysmography through High and low Frequency Information Fusion Attention Mechanism -- Hybrid EEG-fNIRS decoding for fine joint motor imagery of Unilateral Upper Limb with Two-Stage Hybrid Training -- A Neural Network-Augmented Case-Based Reasoning Framework for Weather Risk Modeling using Remote Sensing Data -- Autonomous Design of Floor Plan Based on Architectural Drawings Example without Neighbour Relation -- Using ensemble learning algorithms to integrate multisource remote sensing data for mapping regional forest canopy height -- MTDS: Meta-Path Context Enhanced Drug Combination Synergy Prediction -- A Federated Learning Approach for Genomic Selection in Pigs -- TOP-EEG: a robust software to predict the outcomes of therapies for depression using EEG signals in DGMD domain -- Neural Network as Surrogate Model for Sleep EEG Trajectories and Insomnia Disorder Classification.
• Sommario/riassunto: The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.
• Titolo autorizzato: Neural Information Processing
• ISBN: 981-9670-33-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911011652903321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 2296