Pattern Recognition: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 – October 1, 2021, Proceedings - Couverture souple

9783030926588: Pattern Recognition: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 – October 1, 2021, Proceedings

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ISBN 10 : 3030926583 ISBN 13 : 9783030926588

Editeur : Springer, 2022

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This book constitutes the refereed proceedings of the 43^rd DAGM German Conference on Pattern Recognition, DAGM GCPR 2021, which was held during September 28 - October 1, 2021. The conference was planned to take place in Bonn, Germany, but changed to a virtual event due to the COVID-19 pandemic.

The 46 papers presented in this volume were carefully reviewed and selected from 116 submissions. They were organized in topical sections as follows: machine learning and optimization; actions, events, and segmentation; generative models and multimodal data; labeling and self-supervised learning; applications; and 3D modelling and reconstruction.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer
Date d'�dition: 2022
Langue: anglais
ISBN 10: 3030926583
ISBN 13: 9783030926588
Reliure: Broch�
Num�ro d'�dition: 1
Nombre de pages: 744
�diteur: Bauckhage Christian, Gall Juergen, Schwing Alexander
Coordonn�es du fabricant: ProductSafety@springernature.com
ProductSafety@springernature.com

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Pattern Recognition (eng)

Bauckhage, Christian

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Pattern Recognition

Christian Bauckhage

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 43rd DAGM German Conference on Pattern Recognition, DAGM GCPR 2021, which was held during September 28 - October 1, 2021. The conference was planned to take place in Bonn, Germany, but changed to a virtual event due to the COVID-19 pandemic.The 46 papers presented in this volume were carefully reviewed and selected from 116 submissions. They were organized in topical sections as follows: machine learning and optimization; actions, events, and segmentation; generative models and multimodal data; labeling and self-supervised learning; applications; and 3D modelling and reconstruction. 744 pp. Englisch. N� de r�f. du vendeur 9783030926588

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Pattern Recognition: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 - October 1, 2021, Proceedings (Lecture Notes in Computer Science)

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Pattern Recognition

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the 43rd DAGM German Conference on Pattern Recognition, DAGM GCPR 2021, which was held during September 28 - October 1, 2021.This book constitutes the refereed proceedings of the 43rd DAGM Ger. N� de r�f. du vendeur 525692169

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Pattern Recognition : 43rd Dagm German C

Bauckhage, Christian

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Pattern Recognition: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 ? October 1, 2021, Proceedings (Lecture Notes in Computer Science)

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Pattern Recognition | 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 - October 1, 2021, Proceedings

Christian Bauckhage (u. a.)

Edit� par Springer, 2022

ISBN 10 : 3030926583 ISBN 13 : 9783030926588

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Pattern Recognition

Christian Bauckhage

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ISBN 10 : 3030926583 ISBN 13 : 9783030926588

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Machine Learning and Optimization.- Sublabel-Accurate Multilabeling Meets Product Label Spaces.- InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization.- Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise.- Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data.- Revisiting Consistency Regularization for Semi-Supervised Learning.- Learning Robust Models Using the Principle of Independent Causal Mechanisms.- Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.- Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators.- End-to-end Learning of Fisher Vector Encodings for Part Features in Fine-grained Recognition.- Investigating the Consistency of Uncertainty Sampling in Deep Active Learning.- ScaleNet: An Unsupervised Representation Learning Method for Limited Information.- Actions, Events, and Segmentation.- A New Split for Evaluating True Zero-Shot Action Recognition.- Video Instance Segmentation with Recurrent Graph Neural Networks.- Distractor-Aware Video Object Segmentation.- (SP)^2Net for Generalized Zero-Label Semantic Segmentation.- Contrastive Representation Learning for Hand Shape Estimation.- Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks.- FIFA: Fast Inference Approximation for Action Segmentation.- Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision.- A Comparative Study of PnP and Learning Approaches to Super-Resolution in a Real-World Setting.- Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing.- Spatiotemporal Outdoor Lighting Aggregation on Image Sequences.- Generative Models and Multimodal Data.- AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style.- Learning Conditional Invariance through Cycle Consistency.- CAGAN: Text-To-Image Generation with Combined Attention Generative Adversarial Networks.- TxT: Crossmodal End-to-End Learning with Transformers.- Diverse Image Captioning with Grounded Style.- Labeling and Self-Supervised Learning.- Leveraging Group Annotations in Object Detection Using Graph-Based Pseudo-Labeling.- Quantifying Uncertainty of Image Labelings Using Assignment Flows.- Implicit and Explicit Attention for Zero-Shot Learning.- Self-Supervised Learning for Object Detection in Autonomous Driving.- Assignment Flows and Nonlocal PDEs on Graphs.- Applications.- Viewpoint-Tolerant Semantic Segmentation for Aerial Logistics.- T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression.- TetraPackNet: Four-Corner-Based Object Detection in Logistics Use-Cases.- Detecting Slag Formations with Deep Convolutional Neural Networks.- Virtual Temporal Samples for Recurrent Neural Networks: applied to semantic segmentation in agriculture.- Weakly Supervised Segmentation Pre-training for Plant Cover Prediction.- How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation .- 3D Modeling and Reconstruction.- Clustering Persistent Scatterer Points Based on a Hybrid Distance Metric.- CATEGORISE: An Automated Framework for Utilizing the Workforce of the Crowd for Semantic Segmentation of 3D Point Clouds.- Zero-Shot remote sensing image super resolution based on image continuity and self-tessellations.- A Comparative Survey of Geometric Light Source Calibration Methods.- Quantifying point cloud realism through adversarially learned latent representations.- Full-Glow: Fully conditional Glow for more realistic image generation.- Multidirectional Conjugate Gradients for Scalable Bundle Adjustment.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 744 pp. Englisch. N� de r�f. du vendeur 9783030926588

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