Focal CTC Loss for Chinese Optical Character Recognition on Unbalanced Datasets
In this paper, we propose a novel deep model for unbalanced distribution Character Recognition by employing focal loss based connectionist temporal classification (CTC) function. Previous works utilize Traditional CTC to compute prediction losses. However, some datasets may consist of extremely unba...
Saved in:
| Main Authors: | Xinjie Feng, Hongxun Yao, Shengping Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/9345861 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automated compilation of Urdu poetry handwritten image datasets for optical character recognition
by: Irtaza Ijaz, et al.
Published: (2025-06-01) -
Empowering Dysarthric Communication: Hybrid Transformer-CTC-Based Speech Recognition System
by: R. Vinotha, et al.
Published: (2025-01-01) -
CAPTCHA Recognition Method Based on CNN with Focal Loss
by: Zhong Wang, et al.
Published: (2021-01-01) -
OHSCR: Benchmarks Dataset for Offline Handwritten Sindhi Character Recognition
by: Jakhro Abdul Naveed, et al.
Published: (2024-05-01) -
Radar Waveform Recognition With ConvNeXt and Focal Loss
by: Liping Luo, et al.
Published: (2024-01-01)