000 06130nam a22004215i 4500
999 _c368166
_d368166
_x1
001 368166
003 ES-MaUEC
005 20230102121714.0
006 a||||fo|||| 00| 0
007 cr nn 008mamaa
008 220113s2021 sz | s |||| 0|eng d
020 _a9783030926595
024 7 _a10.1007/978-3-030-92659-5
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aTK7882 .P3
_b2021 EB
245 0 0 _aPattern Recognition :
_b43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 - October 1, 2021, Proceedings
_cedited by Christian Bauckhage, Juergen Gall, Alexander Schwing
250 _aFirst edition 2021
264 1 _aCham
_bSpringer International Publising
_c2021
300 _a1 recurso en línea (XVII, 726 páginas)
_b98 ilustraciones
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aarchivo de texto
_bPDF
490 0 _aImage Processing Computer Vision Pattern Recognition and Graphics
_v13024
505 0 _aMachine 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.
520 _aThis 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.
988 _aSpringer_Computer_2022
650 7 _2embne
_9152614
_aReconocimiento de formas
_vCongresos
700 1 _aBauckhage, Christian
_eeditor literario
700 1 _aGall, Juergen
_eeditor literario
700 1 _aSchwing, Alexander
_eeditor literario
773 0 _tSpringer Nature eBook
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-92659-5
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
_n0
998 _b03/2022
_dz
_eu
_zSI