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| Link zu diesem Datensatz | https://d-nb.info/1342300033 |
| Art des Inhalts | Konferenzschrift |
| Titel | Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VIII / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Person(en) |
Wand, Michael (Herausgeber) Malinovská, Kristína (Herausgeber) Schmidhuber, Jürgen (Herausgeber) Tetko, Igor (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2024 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2024 |
| Umfang/Format | Online-Ressource, XXXIV, 463 p. 128 illus., 123 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-031-72352-0 Printed edition:: ISBN: 978-3-031-72354-4 |
| Inhalt | -- Biosignal Processing in Medicine and Physiology. -- A deep learning multi-omics framework to combine microbiome and metabolome profiles for disease classification. -- CapsDA-Net: A Convolutional Capsule Domain Adversarial Neural Network for EEG-Based Attention Recognition. -- ComplicaCode: Enhancing Disease Complication Detection in Electronic Health Records through ICD Path Generation. -- Depression detection based on multilevel semantic features. -- Depression Diagnosis and Analysis via Multimodal Multi-order Factor Fusion. -- Identify Disease-associated MiRNA-miRNA Pairs through Deep Tensor Factorization and Semi-supervised Learning. -- Interpretable EHR Disease Prediction System Based on Disease Experts and Patient Similarity Graph (DE-PSG). -- Meteorological Data based Detection of Stroke using Machine Learning Techniques. -- OFNN-UNI: Enhanced Optimized Fuzzy Neural Networks based on Unineurons for Advanced Sepsis Classification. -- ProTeM: Unifying Protein Function Prediction via Text Matching. -- SnoreOxiNet: Non-contact Diagnosis of Nocturnal Hypoxemia Using Cross-domain Acoustic Features. -- Unveiling the Potential of Synthetic Data in Sports Science: A Comparative Study of Generative Methods. -- Medical Image Processing. -- Adaptive Fusion Boundary-Enhanced Multilayer Perceptual Network (FBAIM-Net) for Enhanced Polyp Segmentation in Medical Imaging. -- Advancing Free-breathing Cardiac Cine MRI: Retrospective Respiratory Motion Correction Via Kspace-and-Image Guided Diffusion Model. -- Blood Cell Detection and Self-attention-based Mixed Attention Mechanism. -- CellSpot: Deep Learning-Based Efficient Cell Center Detection in Microscopic Images. -- Classification of dehiscence defects in titanium and zirconium dental implants. -- CurSegNet: 3D Dental Model Segmentation Network Based on Curve Feature Aggregation. -- DBrAL: A novel uncertainty-based active learning based on deep-broad learning for medical image classi cation. -- EDPS-SST: Enhanced Dynamic Path Stitching with Structural Similarity Thresholding for Large-Scale Medical Image Stitching under Sparse Pixel Overlap. -- Hop-Gated Graph Attention Network for ASD Diagnosis via PC-Based Graph Regularization Sparse Representation. -- MISS: A Generative Pre-training and Fine-tuning Approach for Med-VQA. -- MSD-HAM-Net: A Multi-modality Fusion Network of PET/CT Images for the Prognosis of DLBCL Patients. -- Multi-Modal Multi-Scale State Space Model for Medical Visual Question Answering. -- Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling. -- Point-based Weakly Supervised 2.5D Cell Segmentation. -- Relative Local Signal Strength: the Impact of Normalization on the Analysis of Neuroimaging Data with Deep Learning. -- SCANet: Dual Attention Network for Alzheimer’s Disease Diagnosis Based on Gated Residual and Spatial Asymmetry Mechanisms. -- SCST: Spatial Consistent Swin Transformer for Multi-Focus Biomedical Microscopic Image Fusion. -- KnowMIM: a self-supervised pre-training framework based on knowledge-guided masked image modeling for retinal vessel segmentation. -- Transferability of Non-Contrastive Self-Supervised Learning to Chronic Wound Image Recognition. -- Two-stage Medical Image-text Transfer with Supervised Contrastive Learning |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2409180424082.325196141888 DOI: 10.1007/978-3-031-72353-7 |
| URL | https://doi.org/10.1007/978-3-031-72353-7 |
| ISBN/Einband/Preis | 978-3-031-72353-7 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Lecture Notes in Computer Science ; 15023 |
| DDC-Notation | 004.3 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 004 Informatik |
| Online-Zugriff | Archivobjekt öffnen |
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