Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20-30, 2023, Proceedings, Part VI (Lecture Notes in Computer Science)

個数:

Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20-30, 2023, Proceedings, Part VI (Lecture Notes in Computer Science)

  • 提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合が若干ございます。
    2. 複数冊ご注文の場合、分割発送となる場合がございます。
    3. 美品のご指定は承りかねます。

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Paperback:紙装版/ペーパーバック版
  • 言語 ENG
  • 商品コード 9789819980758

Full Description

The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. 
The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. 

Contents

MIC: An Effective Defense Against Word-level Textual Backdoor Attacks.- Active Learning for Open-set Annotation Using Contrastive Query Strategy.- Cross-Domain Bearing Fault Diagnosis Method Using Hierarchical Pseudo Labels.- Differentiable Topics Guided New Paper Recommendation.- IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer.- OD-Enhanced Dynamic Spatial-Temporal Graph Convolutional Network for Metro Passenger Flow Prediction.- Enhancing Heterogeneous Graph Contrastive Learning with Strongly Correlated Subgraphs.- DRPDDet: Dynamic Rotated Proposals Decoder for Oriented object detection.- MFSFFuse: Multi-Receptive Field Feature Extraction for Infrared and Visible Image Fusion using Self-Supervised Learning.- Progressive Temporal Transformer for Bird's-Eye-View Camera Pose Estimation.- Adaptive Focal Inverse Distance Transform Maps for Cell Recognition.- Stereo Visual Mesh for Generating Sparse Semantic Maps at High Frame Rates.- Micro-Expression Recognition Based on PCB-PCANet+.- Exploring Adaptive Regression Loss and Feature Focusing in Industrial Scenarios.- Optimal Task Grouping Approach in Multitask Learning.- Effective Guidance in Zero-Shot Multilingual Translation via Multiple Language Prototypes.- Extending DenseHMM with Continuous Emission.- An Efficient Enhanced-YOLOv5 Algorithm for Multi-scale Ship Detection.- Double-Layer Blockchain-Based Decentralized Integrity Verification for Multi-Chain Cross-Chain Data.- Inter-modal Fusion Network with Graph Structure Preserving for Fake News Detection.- Learning to Match Features with Geometry-aware Pooling.- PnP: Integrated Prediction and Planning for Interactive Lane Change in Dense Traffic.- Towards Analyzing the Efficacy of Multi-task Learning in Hate Speech Detection.- Exploring Non-Isometric Alignment Inference for Representation Learning of Irregular Sequences.- Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chain.- Improving GNSS-R Sea Surface Wind Speed Retrieval from FY-3E Satellite Using Multi-Task Learning and Physical Information.- Incorporating Syntactic Cognitive in Multi-granularity Data Augmentation for Chinese Grammatical Error Correction.- Long Short-Term Planning for Conversational Recommendation Systems.- Gated Bi-View Graph Structure Learning.- How Legal Knowledge Graph Can Help Predict Charges for Legal Text.- CMFN: Cross-Modal Fusion Network for Irregular Scene Text Recognition.- Introducing Semantic-based Receptive Field into Semantic Segmentation via Graph Neural Networks.- Transductive Cross-Lingual Scene-Text Visual Question Answering.- Learning Representations for Sparse Crowd Answers.- Identify Vulnerability Types: A Cross-Project Multiclass Vulnerability Classification System based on Deep Domain Adaptation.

最近チェックした商品