LEADER 00840nam 2200253la 450 001 9910482128603321 005 20221107211520.0 035 $a(UK-CbPIL)2090326778 035 $a(CKB)5500000000087886 035 $a(EXLCZ)995500000000087886 100 $a20210618d1488 uy | 101 0 $alat 135 $aurcn||||a|bb| 200 10$aEpistolae familiares Franciscus Philelphus$b[electronic resource] 210 $aDeventer $cRichard Paffraet, 1477-1511$d1488 215 $aOnline resource (4°) 300 $aReproduction of original in Koninklijke Bibliotheek, Nationale bibliotheek van Nederland. 700 $aFilelfo$b Francesco$f1398-1481.$0193895 801 0$bUk-CbPIL 801 1$bUk-CbPIL 906 $aBOOK 912 $a9910482128603321 996 $aEpistolae familiares Franciscus Philelphus$91970067 997 $aUNINA LEADER 07290nam 22007935 450 001 9910983340003321 005 20241117120819.0 010 $a9789819601165$b(electronic bk.) 010 $z9789819601158 024 7 $a10.1007/978-981-96-0116-5 035 $a(MiAaPQ)EBC31784938 035 $a(Au-PeEL)EBL31784938 035 $a(CKB)36590103900041 035 $a(DE-He213)978-981-96-0116-5 035 $a(OCoLC)1472987110 035 $a(EXLCZ)9936590103900041 100 $a20241117d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPRICAI 2024: Trends in Artificial Intelligence $e21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, Kyoto, Japan, November 18?24, 2024, Proceedings, Part I /$fedited by Rafik Hadfi, Patricia Anthony, Alok Sharma, Takayuki Ito, Quan Bai 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (510 pages) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v15281 311 08$aPrint version: Hadfi, Rafik PRICAI 2024: Trends in Artificial Intelligence Singapore : Springer,c2024 9789819601158 327 $a -- Machine Learning. -- Quantitative Analysis of Training Methods, Data Size, and User-Specific Effectiveness in DL-Based Personalized Aesthetic Evaluation. -- 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. High-Order Structure Enhanced Graph Clustering. -- CAFGO: Confidence-Adaptive Factor Graph Optimization Algorithm for Fusion Localization. -- MFNAS: Multi-Fidelity Exploration in Neural Architecture Search with Stable Zero-shot Proxy. -- DyAGL: A Dynamic-aware Adaptive Graph Learning Network for Next POI Recommendation. -- Acoustic classification of bird species using improved pre-trained models. -- Aspect Term Extraction via Dynamic Attention and a Densely Connected Graph Convolutional Network. -- NLDF: Neural Light Dynamic Fields for 3D Talking Head Generation. -- Enhanced Knowledge Tracing via Frequency Integration and Order Sensitivity. -- Position-Aware Dynamic Graph Convolutional Recurrent Network for Traffic Forecasting. -- Pose Preserving Landmark Guided Neural Radiation Fields for Talking Portrait Synthesis. -- Adaptive Optimisation of PyTorch Memory Pools for DNNs. -- Detaching Range from Depth: Personalized Recommendation Meets Personalized PageRank. -- Context-Aware Structural Adaptive Graph Neural Networks. -- multi-GAT: Integrative Analysis of scRNA-seq and scATAC-seq Data Using Graph Attention Networks for Cell Annotation. 330 $aThe five-volume proceedings set LNAI 15281-15285, constitutes the refereed proceedings of the 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, held in Kyoto, Japan, in November 18?24, 2024. The 145 full papers and 35 short papers included in this book were carefully reviewed and selected from 543 submissions. The papers are organized in the following topical sections: Part I: Machine Learning, Deep Learning Part II: Deep Learning, Federated Learning, Generative AI, Natural Language Processing, Large Language Models, Part III: Large Language Models, Computer Vision Part IV: Computer Vision, Autonomous Driving, Agents and Multiagent Systems, Knowledge Graphs, Speech Processing, Optimization Part V: Optimization, General Applications, Medical Applications, Theoretical Foundations of AI. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v15281 606 $aArtificial intelligence 606 $aComputers 606 $aComputer networks 606 $aSocial sciences$xData processing 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aPattern recognition systems 606 $aArtificial Intelligence 606 $aComputing Milieux 606 $aComputer Communication Networks 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aAutomated Pattern Recognition 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aComputer networks. 615 0$aSocial sciences$xData processing. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aPattern recognition systems. 615 14$aArtificial Intelligence. 615 24$aComputing Milieux. 615 24$aComputer Communication Networks. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aAutomated Pattern Recognition. 676 $a006.3 700 $aHadfi$b Rafik$01782728 701 $aAnthony$b Patricia$01782729 701 $aSharma$b Alok$01782730 701 $aIto$b Takayuki$0908181 701 $aBai$b Quan$01782731 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910983340003321 996 $aPRICAI 2024: Trends in Artificial Intelligence$94309238 997 $aUNINA