Antonacopoulos / Chaudhuri / Pal | Pattern Recognition | Buch | 978-3-031-78103-2 | sack.de

Buch, Englisch, 464 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 756 g

Reihe: Lecture Notes in Computer Science

Antonacopoulos / Chaudhuri / Pal

Pattern Recognition

27th International Conference, ICPR 2024, Kolkata, India, December 1-5, 2024, Proceedings, Part XXVIII
Erscheinungsjahr 2024
ISBN: 978-3-031-78103-2
Verlag: Springer Nature Switzerland

27th International Conference, ICPR 2024, Kolkata, India, December 1-5, 2024, Proceedings, Part XXVIII

Buch, Englisch, 464 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 756 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-031-78103-2
Verlag: Springer Nature Switzerland


The multi-volume set of LNCS books with volume numbers 15301-15333 constitutes the refereed proceedings of the 27th International Conference on Pattern Recognition, ICPR 2024, held in Kolkata, India, during December 1–5, 2024.

The 963 papers presented in these proceedings were carefully reviewed and selected from a total of 2106 submissions. They deal with topics such as Pattern Recognition; Artificial Intelligence; Machine Learning; Computer Vision; Robot Vision; Machine Vision; Image Processing; Speech Processing; Signal Processing; Video Processing; Biometrics; Human-Computer Interaction (HCI); Document Analysis; Document Recognition; Biomedical Imaging; Bioinformatics

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Optimizing Personalized Robot Actions with Ranking of Trajectories.- Synthesizing operationally safe controllers for human-in-the-loop human-in-the-plant hybrid close loop systems.- Multi-Frequency Fine-Grained Matching for Audio-Visual Segmentation.- Confidence-Guided Feature Alignment for  Cloth-Changing Person Re-identification.- Fair Latent Representation Learning with Adaptive Reweighing.- FineFACE: Fair Facial Attribute Classification Leveraging Fine-grained Features.- One-factor Cancelable Biometric Template Protection Scheme for Real-valued Features.- Multi-Teacher Invariance Distillation for Domain-Generalized Action Recognition.- ALS-HAR: Harnessing Wearable Ambient Light Sensors to Enhance IMU-based Human Activity Recognition.- Spatio-Temporal Domain-Aware Network for Skeleton-based Action Representation Learning.- Project and Pool: An Action Localization network for localizing actions in Untrimmed Videos.- Multi-Teacher Importance Preserving Knowledge Distillation for Early Violence Prediction.- Improving Temporal Action Segmentation and Detection with Hierarchical Task Grammar.- Hybrid Human Action Anomaly Detection based on Lightweight GNNs and Machine Learning.- Zero-Shot Spatio-Temporal Action Detection by Enhancing Context-Relation Capability of Vision-Language Models.- Nonlinear progressive denoising: a universal regularized denoising strategy for low PSNR images.- Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement.- Composite Concept Extraction through Backdooring.- Guided SAM: Label-Efficient Part Segmentation.- Multidimensional Cross-Reconstructed Networks  for Few-Shot Fine-Grained Image Classification.- Symmetric masking strategy enhances the performance of Masked Image Modeling.- Multiplicative RMSprop using gradient normalization for learning acceleration.- TADIL: Task-Agnostic Domain-Incremental Learning through Task-ID Inference using Transformer Nearest-Centroid Embeddings.- Evidential Federated Learning for Skin Lesion Image Classification.- Adaptive Text Feature Updating for Visual-Language Tracking.- TrajDiffuse: A Conditional Diffusion Model for Environment-Aware Trajectory Prediction.- Principal Graph Neighborhood Aggregation for Underwater Moving Object Detection.- Dynamic Loss Decay based Robust Oriented Object Detection on Remote Sensing Images with Noisy Labels.- Environment-Independent Fusion for Robust Object Detection in Adverse Environments.- Transformer-based RGB and LiDAR Fusion for Enhanced Object Detection.



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