rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Pattern Recognition
    sub title: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 - October 1, 2021, Proceedings
  name:
    name part: Bauckhage, Christian.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Gall, Juergen.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Schwing, Alexander.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2021
    edition: 1st ed. 2021.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XVII, 726 pages 98 illustrations)
  abstract: 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.
  table of contents: 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 wi…
  note: edited by Christian Bauckhage, Juergen Gall, Alexander Schwing.
  subject:
    topic: Pattern recognition systems
  subject:
    topic: Machine learning
  subject:
    topic: Computer vision
  subject:
    topic: Computer engineering
  subject:
    topic: Computer networks
  subject:
    topic: Social sciences-Data processing
  subject:
    topic: Education-Data processing
  subject:
    topic: Automated Pattern Recognition
  subject:
    topic: Machine Learning
  subject:
    topic: Computer Vision
  subject:
    topic: Computer Engineering and Networks
  subject:
    topic: Computer Application in Social and Behavioral Sciences
  subject:
    topic: Computers and Education
  classification: Q337.5
  classification: TK7882.P3
  classification: 006.4
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 13024
  identifier: 9783030926595
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 220113
    record change date: 20230330185254.3
    record identifier: in00004556628