Amanote Research

Amanote Research

    RegisterSign In

Feature-Enriched Character-Level Convolutions for Text Regression

doi 10.18653/v1/w17-4765
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2017

Authors
Gustavo PaetzoldLucia Specia
Publisher

Association for Computational Linguistics


Related search

A Character-Level Error Analysis Technique for Evaluating Text Entry Methods

2002English

Character Feature Learning for Named Entity Recognition

IEICE Transactions on Information and Systems
Electronic EngineeringPattern RecognitionHardwareComputer VisionElectricalArchitectureArtificial IntelligenceSoftware
2018English

Mathematical Model for Single Character Cipher Text

2019English

Ensemble Logistic Regression for Feature Selection

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2011English

Univalence for Convolutions

International Journal of Mathematics and Mathematical Sciences
Mathematics
1996English

Condition Estimation for Regression and Feature Selection

Journal of Computational and Applied Mathematics
Computational MathematicsApplied Mathematics
2020English

A Modified Direction Feature for Cursive Character Recognition

English

Synthetically Supervised Feature Learning for Scene Text Recognition

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2018English

Topographic Feature Extraction for Bengali and Hindi Character Images

Signal & Image Processing : An International Journal
2011English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy