Fr. 123.00

MultiMedia Modeling - 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 - February 2, 2024, Proceedings, Part III

Englisch · Taschenbuch

Versand in der Regel in 1 bis 2 Wochen (Titel wird auf Bestellung gedruckt)

Beschreibung

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This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29-February 2, 2024.
The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.

Inhaltsverzeichnis

Global-to-Local Feature Mining Network for RGB-Infrared Person Re-Identification.- Semantic Transition Detection for Self-Supervised Vide Scene Segmentation.- Multi-Task Collaborative Network for Image-text Retrieval.- FGENet:Fine-Grained Extraction Network for Congested Crowd Counting.- MSMV-UNet : A 2.5D Stroke Lesion Segmentation Method based on Multi-slice Feature Fusion.- Non-Local Spatial-Wise and Global Channel-Wise Transformer forEfficient Image Super-Resolution.- MobileViT-FocR: MobileViT with Fixed-One-Centre Loss and Gradient Reversal for Generalised Fake Face Detection.- ASF-Conformer: Audio Scoring Conformer with FFC for Speaker Verification in Noisy Environments.- Prior-Knowledge-Free Video Frame Interpolation with Bidirectional Regularized Implicit Neural Representations.- Two-Stage Reasoning Network with Modality Decomposition for TextVQA.- Localization and Local Motion Magnification of Pulsatile Regions in Endoscopic Surgery Videos.- Co-speech Gesture Generation with Variational Auto Encoder.- Differentiable Neural Architecture Search Based on Efficient Architecture for Lightweight Image Super-Resolution.- Learning Collaborative Reinforcement Attention for 3D Face Reconstruction and Dense Alignment.- Exploring Multi-Modal Fusion for Image Manipulation Detection and Localization.- Object-based Spatio-Temporal Heterogeneous Network for VideoQA.- Adaptive Token Selection and Fusion Network for Multimodal Sentiment Analysis.- Exploring Imperceptible Adversarial Examples in YCbCr Color Space.- Fractional-order image moments and applications.- Time-Quality Tradeoff of MuseHash Query Processing Performance.- Dual-Fisheye Image Stitching via Unsupervised Deep Learning.- CA-GAN: Conditional Adaptive Generative Adversarial Network for Text-to-Image Synthesis.- RDC-YOLOv5:Improved Safety Helmet Detection in Adverse Weather.- Sustainable Commercial Fishery Control using Multimedia Forensics Data from Non-trusted, Mobile Edge Nodes.- MC-TCMNER: A Multi-Modal Fusion Model Combining Contrast Learning Method for Traditional Chinese Medicine NER.- C3-PO: A Convolutional Neural Network for COVID Onset Predictionfrom Cough Sounds.- Pseudo-label based Unsupervised Momentum Representation Learning for Multi-domain Image Retrieval.- DFGait: Decomposition Fusion Representation Learning for Multimodal Gait Recognition.-  MoPE: Mixture of Pooling Experts Framework for Image-Text Retrieval.- Multi-Modal Video Topic Segmentation with Dual-Contrastive Domain Adaptation.- Unsupervised Multi-Collaborative Learning Network for 3D Face Reconstruction.- A Region Based Non-overlapping Reference Speech Estimation Method for Speaker Extraction.- Self-Supervised Edge Structure Learning forMulti-View Stereo and Parallel Optimization.- Prototype-Enhanced Hypergraph Learning for Heterogeneous Information Networks.- A Language-based solution to enable Metaverse Retrieval.- Part-aware Prompt Tuning For Weakly Supervised Referring Expression Grounding.- Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning.- A Multidimensional Taxonomy Model for Music Tangible User Interfaces.

Produktdetails

Mitarbeit Alan Hanjalic (Herausgeber), Björn Þór Jónsson (Herausgeber), Cynthia Liem (Herausgeber), Cynthia Liem et al (Herausgeber), Bei Liu (Herausgeber), Stevan Rudinac (Herausgeber), Marcel Worring (Herausgeber), Yoko Yamakata (Herausgeber)
Verlag Springer, Berlin
 
Sprache Englisch
Produktform Taschenbuch
Erschienen 28.01.2024
 
EAN 9783031533105
ISBN 978-3-0-3153310-5
Seiten 535
Abmessung 155 mm x 29 mm x 235 mm
Illustration XVIII, 535 p. 180 illus., 171 illus. in color.
Serie Lecture Notes in Computer Science
Thema Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Anwendungs-Software

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