9789819981830 - neural information processing: 30th international conference, iconip 2023, changsha, china, november 20–23, 2023, proceedings, part xv: 1969 (12 risultati)
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Paperback. Condizione: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
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Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2024
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Condizione: New. pp. 536 1st ed. 2024 edition NO-PA16APR2015-KAP.
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Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 499 | Sprache: Englisch | Produktart: Bücher | The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedi…ngs set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
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Taschenbuch. Condizione: Neu. Neural Information Processing | 30th International Conference, ICONIP 2023, Changsha, China, November 20-23, 2023, Proceedings, Part XV | Biao Luo (u. a.) | Taschenbuch | xx | Englisch | 2024 | Springer | EAN 9789819981830 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17,… 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023.The1274papers presented in the proceedings set were carefully re…viewed and selected from652submissions.The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
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Softcover. Condizione: gut. 2023. Neural Information Processing: 30th International Conference, Iconip 2023, Changsha, China, November 20-23, 2023, Proceedings, Part IX In deutscher Sprache. pages.
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Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore Nov 2023, 2023
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023.The1274papers presented in the proceedings set w…ere carefully reviewed and selected from652submissions.The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. 536 pp. Englisch.
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿Applications.- Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation.- RF-Based Drone Detection and Identification with Deep Neural Network: Review and Case Study.- Effective skill learning on vascular robot…ic systems: Combining offline and online reinforcement learning.- Exploring Efficient-Tuned Learning Audio Representation Method from BriVL.- Can You Really Reason: A Novel Framework for Assessing Natural Language Reasoning Datasets and Models.- End-to-End Urban Autonomous Navigation with Decision Hindsight.- Identifying Self-Admitted Technical Debt with Context-based Ladder Network.- NDGR: A Noise Divide and Guided Re-labeling Framework for Distantly Supervised Relation Extraction.- Customized Anchors Can Better Fit the Target in Siamese Tracking.- Can We Transfer Noise Patterns A Multi-environment Spectrum Analysis Model Using Generated Cases.- Progressive Supervision for Tampering Localization in Document Images.- Multi-granularity Deep Vulnerability Detection using Graph Neural Networks.- Rumor Detection with Supervised Graph Contrastive Regularization.- A Meta Learning-based Training Algorithm for Robust Dialogue Generation.- Effects of Brightness and Class-unbalanced Dataset on CNN Model Selection and Image Classification considering Autonomous Driving.- HANCaps: A Two-Channel Deep Learning Framework for Fake News Detection in Thai.- Pre-trained Financial Model for Price Movement Forecasting.- Impulsion of Movie's Content-Based Factors in Multi-Modal Movie Recommendation System.- Improving Transferbility of Adversarial Attack on Face Recognition with Feature Attention.- Dendritic Neural Regression Model Trained by Chicken Swarm Optimization Algorithm for Bank Customer Churn Prediction.- BERT-LBIA: A BERT-Based Late Bidirectional Interaction Attention Model for Legal Case Retrieval.- Learning Discriminative Semantic and Multi-View Context for Domain Adaptive Few-shot Relation Extraction.- ML2FNet: A Simple but Effective Multi-Level Feature Fusion Network for Document-Level Relation Extraction.- Implicit Clothed Human Reconstruction Based on Self-attention and SDF.- Privacy-Preserving Federated Compressed Learning Against Data Reconstruction Attacks Based on Secure Data.- An Attack Entity Deducing Model for Attack Forensics.- Semi-supervised classification on data streams with recurring concept drift based on conformal prediction.- Zero-shot Relation Triplet Extraction via Retrieval-Augmented Synthetic Data Generation.- Parallelizable Simple Recurrent Units with Hierarchical Memory.- Enhancing Legal Judgment Prediction with Attentional Networks Utilizing Legal Event Types.- MOOCs Dropout Prediction via Classmates Augmented Time-Flow Hybrid Network.- Multiclass Classification and Defect Detection of Steel tube using modified YOLO.- GACE: Learning Graph-Based Cross-Page Ads Embedding For Click-Through Rate Prediction.- TEZARNet : TEmporal Zero-shot Activity Recognition Network.- Tigrinya OCR: Applying CRNN for Text Recognition.- Generating Pseudo-Labels for Car Damage Segmentation using Deep Spectral Method.- Two-Stage Graph Convolutional Networks for Relation Extraction.- Multi-vehicle Platoon Overtaking Using NoisyNet Multi-Agent Deep Q-Learning Network.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 536 pp. Englisch.
