# Attention-based Fully Gated CNN-BGRU for Russian Handwritten Text

arXiv: https://arxiv.org/abs/2008.05373 · HTML: https://mlsanity.com/paper/2008.05373/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2020.

## Built on by (most cited first, 17 of 17)

- [TNCR: Table Net Detection and Classification Dataset](https://mlsanity.com/paper/2106.15322/) (2021)
- [Handwritten Text Recognition: A Survey](https://mlsanity.com/paper/2502.08417/) (2025)
- [KOHTD: Kazakh Offline Handwritten Text Dataset](https://mlsanity.com/paper/2110.04075/) (2021)
- [On the Generalization of Handwritten Text Recognition Models](https://mlsanity.com/paper/2411.17332/) (2024)
- [Advancements and Challenges in Arabic Optical Character Recognition: A Comprehensive Survey](https://mlsanity.com/paper/2312.11812/) (2023)
- [Recent Advancements and Challenges of Turkic Central Asian Language Processing](https://mlsanity.com/paper/2407.05006/) (2024)
- [Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models](https://mlsanity.com/paper/2102.04816/) (2021)
- [Customer Profiling, Segmentation, and Sales Prediction using AI in Direct Marketing](https://mlsanity.com/paper/2302.01786/) (2023)
- [StackMix and Blot Augmentations for Handwritten Text Recognition](https://mlsanity.com/paper/2108.11667/) (2021)
- [Handwritten text generation and strikethrough characters augmentation](https://mlsanity.com/paper/2112.07395/) (2021)
- [Spatial Context-based Self-Supervised Learning for Handwritten Text Recognition](https://mlsanity.com/paper/2404.11585/) (2024)
- [A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmasking](https://mlsanity.com/paper/2405.05900/) (2024)
- [DRetHTR: Linear-Time Decoder-Only Retentive Network for Handwritten Text Recognition](https://mlsanity.com/paper/2602.17387/) (2026)
- [CSSL-MHTR: Continual Self-Supervised Learning for Scalable Multi-script Handwritten Text Recognition](https://mlsanity.com/paper/2303.09347/) (2023)
- [Boosting CNN-based Handwriting Recognition Systems with Learnable Relaxation Labeling](https://mlsanity.com/paper/2409.05699/) (2024)
- [Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies](https://mlsanity.com/paper/2604.09713/) (2026)
- [Handwritten Text Recognition Lives in the High-Pixel Variance Subspace](https://mlsanity.com/paper/2609.35473/) (2026)

## Abstract (arXiv)

This research approaches the task of handwritten text with attention encoder-decoder networks that are trained on Kazakh and Russian language. We developed a novel deep neural network model based on Fully Gated CNN, supported by Multiple bidirectional GRU and Attention mechanisms to manipulate sophisticated features that achieve 0.045 Character Error Rate (CER), 0.192 Word Error Rate (WER) and 0.253 Sequence Error Rate (SER) for the first test dataset and 0.064 CER, 0.24 WER and 0.361 SER for the second test dataset. Also, we propose fully gated layers by taking the advantage of multiple the output feature from Tahn and input feature, this proposed work achieves better results and We experimented with our model on the Handwritten Kazakh & Russian Database (HKR). Our research is the first work on the HKR dataset and demonstrates state-of-the-art results to most of the other existing models.