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Produktbild: Data Science and Machine Learning
Band 2765

Data Science and Machine Learning 23rd Australasian Conference, AusDM 2025, Brisbane, QLD, Australia, November 26–28, 2025, Proceedings

Aus der Reihe Communications in Computer and Information Science

73,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

13.02.2026

Abbildungen

XVI, 562 p. 137 illus., 129 illus. in color.

Herausgeber

Quang Vinh Nguyen + weitere

Verlag

Springer Singapore

Seitenzahl

562

Maße (L/B/H)

23,5/15,5/3,2 cm

Gewicht

867 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9567-85-0

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

13.02.2026

Abbildungen

XVI, 562 p. 137 illus., 129 illus. in color.

Herausgeber

Verlag

Springer Singapore

Seitenzahl

562

Maße (L/B/H)

23,5/15,5/3,2 cm

Gewicht

867 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9567-85-0

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Data Science and Machine Learning

  • .- Federated, Adaptive, and Trustworthy Machine Learning.



    .- DAARA: Divergence-Aware Attention for Robust Aggregation in Federated Learning Against Poisoning Attacks.



    .- Understanding the Asymmetric Impact of Forecast Accuracy on Decision Quality.



    .- WaveFSL: Wave Interference-Based Meta-Learning for Few-Shot Cross-Modality Traffic Forecasting.



    .- FedMOAR: Multi-Objective Adaptive Regularization for Fair and Efficient Federated Learning.



    .- Unveiling Reliability in Multi-Omics Classification:Fusion, Calibration, and Dynamic Scaling.



    .- Stability Evaluation of Clusterings Across Time.



    .- DriftSense: Adaptive Drift Detection with Incremental Hoeffding Trees for Real-Time Spatial Crowdsourcing.



    .- Dynamic Meta-Learning Ensemble for Financial Forecasting.



    .- Environment, Information Security and Productivity.



    .- Effective Missing-Data Imputation for Time Series with Seasonality and Causality.



    .- UniCausal: A Unified Approach to Causal Discovery from Hybrid Industrial Time Series and Events.



    .- Dynamic Source Code Vulnerability Characteristics Selection for Enhanced Vulnerability Discover.



    .- Modelling Financial Time Series of Returns and Covariance Matrices Using Time-Space Transformers.



    .- Temporal Fusion of Biophysical and Climate Data: A Data-Driven Hybrid Learning Approach for Short-Term Aboveground Biomass Forecasting.



    .- Precision to Costing: Budgeted Modelling for Customer Contact Prediction.



    .- Defining Responsible AI: Contextual Insights Powered by LLMs.



    .- Deep Learning Fusion and Vision.



    .- Fusing Deep Object Detectors via Spatial Heatmap-Based Relevance Modeling.



    .- CarDamageEval: Benchmark Evaluation of Car Damage Assessment Using Vision Language Models.



    .- Regularizing StyleGAN with Inter-Resolution Residual Pattern Consistency via a Laplacian Pyramid.



    .- Mixup and Local-FOMA based Two-Phase Manifold Augmentation in Image Classification.



    .- BARE: Boundary-Aware with Resolution Enhancement for Tree Crown Delineation.



    .- Integrating Vision Transformers and Autoencoders for Interpretable Cancer Risk Assessment.



    .- LightSkinNet: Lightweight CNN with Attention for Accurate,Mobile-Efficient Multiclass Skin Lesion Classification.



    .- A DenseNet-YOLOv8 Fusion Model for Intelligent Parasite Egg Detection and Classification.



    .- Health and Social Good.



    .- An AI-Driven Framework for Real-Time Reporting and Identification of Lost Cats.



    .- Benchmarking Preprocessing and Integration Methods in Single-Cell Genomics.



    .- Towards Automated Differential Diagnosis of Skin Diseases Using Deep Learning and Imbalance-Aware Strategies.



    .- Causal Recommendation Method for Personalised Chemotherapy Optimisation in Breast Cancer.



    .- Machine Learning for Traffic Accident Prediction: Integrating Spatial and Behavioral Data for Road Safety



    Insights.



    .- Visionary: Enhancing Visual Context for the Visually Impaired.



    .- Knowledge-Driven and Domain Specific AI.



    .- Advancing Atayal Language Preservation with AI-Driven Multimodal Speech and Text Processing.



    .- ETCOD: Embedding-Based Anomaly Detection and LLM-Driven Validation Framework for Knowledge Graphs.



    .- Top-k Ranking with Exact Positional Fairness.



    .- Evaluating Structural Preprocessing in RAG for Academic Curriculum Applications.



    .- Evaluating Cross-Lingual Classification Strategies EnablingTopic Discovery for Multilingual Social Media Data.



    .- From Burst to Routine: Mining Time-Compact Patterns from Sequential Dataset.



    .- A Parameter-free Method Tuning for Multi-scale Wildfire Images Retrieval Task.



    .- NeuroPhysNet: A FitzHugh-Nagumo-Based Physics-InformedNeural Network Framework for Electroencephalograph (EEG)Analysis and Motor Imagery Classification.