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29 795 (0,176s)

Result

K-best Viterbi Semi-supervized Active Learning in Sequence Labelling

and regression tasks, active learning has been also applied to sequence labelling. According to the standard active learning approach, sequences for which the labelling would be the most informative should be ...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2017
  • D
  • Link
Result

Label Attention Network for Structured Prediction

Sequence labeling assigns a label to each token in a sequence, which machine translation can also be transformed into sequence labeling tasks. Neural models have been shown powerful for sequen...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2022
  • Jimp
  • Link
Result

Video Sequence Boundary Labeling with Temporal Coherence

We propose a method for video sequence boundary labeling which maintains to position label boxes in video sequence on a lower number of rows than existing methods video sequences labeling compared...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • D
  • Link
Result

K-best Viterbi Semi-supervized Active Learning in Sequence Labelling

and regression tasks, active learning has been also applied to sequence labelling. According to the standard active learning approach, sequences for which the labelling would be the most informative should be ...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2017
  • Jost
  • Link
Result

Deep Bayesian Semi-Supervised Active Learning for Sequence Labelling

a series of token-level labels for a whole sequence to be available during the training process. Annotators of sequences typically label easily predictable parts of the sequence although such parts could ...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • D
  • Link
Result

Video Sequence Boundary Labeling with Temporal Coherence

We propose a method for video sequence boundary labeling which maintains to position label boxes in video sequence on a lower number of rows than existing methods video sequences labeling compared...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • D
  • Link
Result

Hierarchically-Refined Label Attention Network for Sequence Labeling

CRF has been used as a powerful model for statistical sequence labeling. For neural sequence labeling, however, BiLSTM-CRF does not always lead to better results Markov label transition model of CRF does n...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • O
  • Link
Result

Risk minimization for zero-shot sequence labeling

Zero-shot sequence labeling aims to build a sequence labeler without human models) to generate pseudo-labeled datasets and train a target sequence labeler framework for zero-shot sequ...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2021
  • D
Result

Dependency Parsing as a Sequence Labeling Task

The aim of this paper is to explore the feasibility of solving the dependency parsing problem using sequence labeling tools. We introduce an algorithm to transform a dependency tree into a tag sequence suitable for a se...

AI - Jazykověda

  • 2010
  • Jx
Result

Viable Dependency Parsing as Sequence Labeling

We recast dependency parsing as a sequence labeling problem, exploring several encodings of dependency trees as labels. While dependency parsing by means of sequence labeling had been attempted in existing...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • O
  • Link
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