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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
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| 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 ![]() |
| ISBN: | 3-031-85181-1 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910999675603321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |