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Pattern Recognition : 46th DAGM German Conference, DAGM GCPR 2024, Munich, Germany, September 10–13, 2024, Proceedings, Part I / / edited by Daniel Cremers, Zorah Lähner, Michael Moeller, Matthias Nießner, Björn Ommer, Rudolph Triebel



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Titolo: Pattern Recognition : 46th DAGM German Conference, DAGM GCPR 2024, Munich, Germany, September 10–13, 2024, Proceedings, Part I / / edited by Daniel Cremers, Zorah Lähner, Michael Moeller, Matthias Nießner, Björn Ommer, Rudolph Triebel Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
Edizione: 1st ed. 2025.
Descrizione fisica: 1 online resource (XVII, 365 p. 113 illus., 103 illus. in color.)
Disciplina: 006
Soggetto topico: Image processing - Digital techniques
Computer vision
Artificial intelligence
Computer systems
Education - Data processing
Application software
Computer Imaging, Vision, Pattern Recognition and Graphics
Artificial Intelligence
Computer System Implementation
Computers and Education
Computer and Information Systems Applications
Persona (resp. second.): CremersDaniel
LähnerZorah
MoellerMichael
NießnerMatthias
OmmerBjörn
TriebelRudolph
Nota di contenuto: -- Clustering and Segmentation. -- PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks. -- A State-of-the-Art Cutting Plane Algorithm for Clique Partitioning. -- Self-Supervised Semantic Segmentation from Audio-Visual Data. -- BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation. -- Learning Techniques. -- FullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks. -- Self-Masking Networks for Unsupervised Adaptation. -- A Theoretical Formulation on the Use of Multiple Positive Views in Contrastive Learning -- Decoupling of neural network calibration measures. -- Examining Common Paradigms in Multi-Task Learning. -- DIAGen: Semantically Diverse Image Augmentation with Generative Models for Few-Shot Learning. -- Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval .. -- Anomaly Detection with Conditioned Denoising Diffusion Models. -- Medical and Biological Applications. -- SurgeoNet: Realtime 3D Pose Estimation of Articulated Surgical Instruments from Stereo Images using a Synthetically-trained Network. -- Foundation Models Permit Retinal Layer Segmentation Across OCT Devices. -- Correlation Clustering of Organoid Images. -- Animal Identification with Independent Foreground and Background Modeling. -- Robust Tumor Segmentation with Hyperspectral Imaging and Graph Neural Networks. -- Bigger Isn’t Always Better: Towards a General Prior for Medical Image Reconstruction. -- Uncertainty and Explainability. -- Latent Diffusion Counterfactual Explanations. -- Enhancing Surface Neural Implicits with Curvature-Guided Sampling and Uncertainty-Augmented Representations. -- Uncertainty Voting Ensemble for Imbalanced Deep Regression. -- Analytical Uncertainty-Based Loss Weighting in Multi-Task Learning.
Sommario/riassunto: This 2-volume set LNCS 15297-15298 constitutes the refereed proceedings of the 46th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2024, held in Munich, Germany, during September 10-13, 2024. The 44 full papers included in these proceedings were carefully reviewed and selected from 81 submissions. They are organized in these topical sections: Part I: Clustering and Segmentation; Learning Techniques; Medical and Biological Applications; Uncertainty and Explainability. Part II: Modelling of Faces and Shapes; Image Generation and Reconstruction; 3D Analysis and Sythesis; Video Analysis; Photogrammetry and Remote Sensing.
Titolo autorizzato: Pattern Recognition  Visualizza cluster
ISBN: 3-031-85181-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910999675603321
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Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 15297