A Benchmark Dataset and a Framework for Urdu Multimodal Named Entity Recognition
The emergence of multimodal content, particularly text and images on social media, has positioned Multimodal Named Entity Recognition (MNER) as an increasingly important area of research within Natural Language Processing. Despite progress in high-resource languages such as English, MNER remains und...
Saved in:
| Main Authors: | Hussain Ahmad, Qingyang Zeng, Jing Wan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11025808/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
B-NER: A Novel Bangla Named Entity Recognition Dataset With Largest Entities and Its Baseline Evaluation
by: Md. Zahidul Haque, et al.
Published: (2023-01-01) -
UMEDNet: a multimodal approach for emotion detection in the Urdu language
by: Adil Majeed, et al.
Published: (2025-05-01) -
Entity-level cross-modal fusion for multimodal chinese agricultural diseases and pests named entity recognition
by: Jingzhong Huang, et al.
Published: (2025-12-01) -
UrduSER: A comprehensive dataset for speech emotion recognition in Urdu languageMendeley Data
by: Muhammad Zaheer Akhtar, et al.
Published: (2025-06-01) -
A Dual-Enhanced Hierarchical Alignment Framework for Multimodal Named Entity Recognition
by: Jian Wang, et al.
Published: (2025-05-01)