9789819981403 - Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20?23, 2023, Proceedings, Part X: 1964 (10 risultati)

Condizione: Good. Has some wear and creases. Has a remainder mark. paperback Used - Good 2023.

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Condizione: New. pp. 632 1st ed. 2024 edition NO-PA16APR2015-KAP.

Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 591 | 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 proceedings 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.

Paperback. Condizione: Brand New. 630 pages. 9.26x6.10x1.27 inches. In Stock.

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 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.

Condizione: new. Questo è un articolo print on demand.

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 were 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. 632 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.&nbsp&nbspThe&nbsp1274&nbsppapers .

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿Human Centred Computing.- Paper Recommendation with Multi-View Knowledge-aware Attentive Network.- Biological Tissue Sections Instance Segmentation based on Active Learning.- Research on automatic segmentation algorithm of brain tumor image based on multi-sequence self-supervised fusion in complex scenes.- An Effective Morphological Analysis Framework of Intracranial Artery in 3D Digital Subtraction Angiography.- Effective Domain Adaptation for Robust Dysarthric Speech Recognition.- TCNet: Texture and Contour-Aware Model for Bone Marrow Smear Region of Interest Selection.- Diff-Writer: A Diffusion Model Based Stylized Online Handwritten Chinese Character Generator.- EEG epileptic seizure classification using hybrid time-frequency attention deep network.- A Feature Pyramid Fusion Network Based on Dynamic Perception Transformer for Retinal OCT Biomarker Image Segmentation.- LDW-RS Loss: Label Density-Weighted Loss with Ranking Similarity Regularization for Imbalanced Deep Fetal Brain Age Regression.- Segment Anything Model for Semi-Supervised Medical Image Segmentation via selecting reliable pseudo-labels.- Aided diagnosis of autism spectrum disorder based on a mixed neural network model.- A Supervised Spatio-Temporal Contrastive Learning Framework with Optimal Skeleton Subgraph Topology for Human Action Recognition.- Multi-Scale Feature Fusion Neural Network for Accurate Prediction of Drug-Target Interactions.- GoatPose: A Lightweight and Efficient Network with Attention Mechanism.- Sign Language Recognition for Low Resource Languages using Few Shot Learning.- T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer Classification.- Weakly Supervised Temporal Action Localization Through Segment Contrastive Learning.- S-CGRU: An Efficient Model for Pedestrian Trajectory Prediction.- Prior-Enhanced Network for Image-based PM2.5 Estimation from Imbalanced Data Distribution.- Dynamic Data Augmentation via Monte-Carlo Tree Search for Prostate MRI Segmentation.- Language Guided Graph Transformer for Skeleton Action Recognition.- A Federated Multi-Stage Light-Weight Vision Transformer for Respiratory Disease Detection.- Curiosity Enhanced Bayesian Personalized Ranking for Recommender Systems.- Modeling online adaptive navigation in virtual environments based on PID control.- LIP READING USING TEMPORAL ADAPTIVE MODULE.- AudioFormer: Channel Audio Encoder Based on Multi-Granularity Features.- A Context Aware Lung Cancer Survival Prediction Network by Using Whole Slide Images.- A Novel Approach for Improved Pedestrian Walking Speed Prediction: Exploiting Proximity Correlation.- MView-DTI: A multi-view feature fusion-based approach for drug-target protein interaction prediction.- User Multi-Preferences Fusion for Conversational Recommender Systems.- Debiasing MedicationRecommendation with Counterfactual Analysis.- Detecting Depression and Alcoholism Disorders by EEG Signal.- Unleash the Capabilities of the Vision-Language Pre-training Model in Gaze Object Prediction.- A Two-Stage Network for Segmentation of Vertebrae and Intervertebral Discs: Integration of Efficient Local-Global Fusion Using 3D Transformer and 2D CNN.- Integrating Multi-View Feature Extraction and Fuzzy Rank-Based Ensemble for Accurate HIV-1 Protease Cleavage Site Prediction.- KSHFS: Research on Drug-Drug Interaction Prediction Based on Knowledge Subgraph and High-order Feature-aware Structure.- Self-Supervised-Enhanced Dual Hierarchical Graph Convolution Network for Social Recommendation.- Dynamical Graph Echo State Networks with Snapshot Merging for Spreading Process Classification.- TrajecSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 632 pp. Englisch.