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ENTITY Convolutional Recurrent Neural Network

Convolutional Recurrent Neural Network

PulseAugur coverage of Convolutional Recurrent Neural Network — every cluster mentioning Convolutional Recurrent Neural Network across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_187489 ·

    VLMs map 20th-century Armenian diaspora ads from historical French press

    Researchers have developed a novel pipeline to extract and geocode commercial advertisements from digitized 20th-century Armenian newspapers in France. This system utilizes vision-language models (VLMs) to overcome the …

  2. RESEARCH · CL_97626 ·

    New dataset and CRNN model advance Urdu handwritten text recognition

    Researchers have introduced the Urdu Katib Handwritten Dataset (UKHD), the first offline dataset of historical Urdu handwritten text lines. This dataset aims to address the scarcity of resources for Urdu Handwritten Tex…

  3. TOOL · CL_97640 ·

    HTR systems show persistent performance gap for Arabic vs. Latin scripts

    A new study published on arXiv analyzes the performance gap between handwritten text recognition (HTR) systems for Latin and Arabic scripts. Researchers used a unified Convolutional Recurrent Neural Network (CRNN) model…

  4. TOOL · CL_93989 ·

    New framework boosts Arabic HTR dataset quality with AI and human review

    Researchers have developed a novel two-stage framework, CER-HV, designed to improve the quality of datasets used for training Handwritten Text Recognition (HTR) models, particularly for Arabic-script languages. The fram…

  5. RESEARCH · CL_22407 ·

    Cross-language HTR models improve low-resource performance via sequence modeling

    Researchers have investigated how cross-language transfer learning improves Handwritten Text Recognition (HTR) for low-resource Arabic-script languages. Their studies indicate that sequence modeling, rather than just sh…

  6. RESEARCH · CL_02078 ·

    Neural networks simulate crystal growth dynamics with variable supersaturation

    Researchers have developed Convolutional Recurrent Neural Network surrogate models to simulate crystal growth dynamics. These models are trained on data from Allen-Cahn dynamics and can account for variable supersaturat…