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Neural Information Processing: 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 26, 2024, Proceedings, Part XV [Mīkstie vāki]

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  • Formāts: Paperback / softback, 436 pages, height x width: 235x155 mm, 146 Illustrations, color; 14 Illustrations, black and white; XXXIV, 436 p. 160 illus., 146 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2296
  • Izdošanas datums: 24-Jun-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819670322
  • ISBN-13: 9789819670321
  • Mīkstie vāki
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  • Formāts: Paperback / softback, 436 pages, height x width: 235x155 mm, 146 Illustrations, color; 14 Illustrations, black and white; XXXIV, 436 p. 160 illus., 146 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2296
  • Izdošanas datums: 24-Jun-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819670322
  • ISBN-13: 9789819670321
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.
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 Alzheimers 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.