Produktbild: PRICAI 2024: Trends in Artificial Intelligence
Band 15281

PRICAI 2024: Trends in Artificial Intelligence 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, Kyoto, Japan, November 18–24, 2024, Proceedings, Part I

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.11.2024

Herausgeber

Rafik Hadfi + weitere

Verlag

Springer Singapore

Seitenzahl

489

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

774 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9601-15-8

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.11.2024

Herausgeber

Verlag

Springer Singapore

Seitenzahl

489

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

774 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9601-15-8

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: PRICAI 2024: Trends in Artificial Intelligence
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    .- EQUISCALE: Equitable Scaling for Abstention Learning.

    .- Unsupervised Clustering Using a Variational Autoencoder with Constrained Mixtures for Posterior and Prior.

    .- UTBoost: Gradient Boosted Decision Trees for Uplift Modeling.

    .- CodeMosaic Patch: Physical Adversarial Attacks Against Infrared Aerial Object Detectors.

    .- Sequential Clustering for Real-world Datasets.

    .- Dual-mode Contrastive Learning-Enhanced Knowledge Tracing.

    .- Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks.

    .- Characterization of Similarity Metrics in Epistemic Logic.

    .- A Relaxed Symmetric Non-negative Matrix Factorization Approach for Community Discovery.

    .- Enhanced Cognitive Distortions Detection and Classification through Data Augmentation Techniques.

    .- Enhancing Music Genre Classification using Augmented Features Ensemble Learning Technique.

    .- A Multi-Layer Network Community Detection Method via Network Feature Augmentation and Contrastive Learning.

    .- Scene Text Recognition Based on Corner Point and Attention Mechanism.

    .- A Comprehensive Framework for Debiased Sample Selection across All Noise Types.

    .- A Traffic Flow Prediction Model Integrating Dynamic Implicit Graph Information.

    .- A Recursive Learning Algorithm for the Least Squares SVM.

    .- BDEL: A Backdoor Attack Defense Method Based on Ensemble Learning.

    .- Customizing Spatial-Temporal Graph Mamba Networks for Pandemic Forecasting.

    .- Distribution-aligned Sequential Counterfactual Explanation with Local Outlier Factor.

    .- T-FIA: Temporal-Frequency Interactive Attention Network for Long-term Time Series Forecasting.

    .- Multi-modal Food Recommendation using Clustering andSelf-supervised Learning.

    .- A quality assessment method of few-shot datasets based on the fusion of quantity and quality.

    .- Deep Learning.

    .- CSDCNet: A Semantic Segmentation Network for Tubular Structures.

    .- Neural Network Surrogate based on Binary Classification for Assisting Genetic Programming in Searching Scheduling Heuristic.

    .- HN-Darts:Hybrid Network Differentiable Architecture Search for Industrial Scenarios.

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    .- CAFGO: Confidence-Adaptive Factor Graph Optimization Algorithm for Fusion Localization.

    .- MFNAS: Multi-Fidelity Exploration in Neural Architecture Search with Stable Zero-shot Proxy.

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