arXiv (All)
open access
BDSLI: A hybrid CNN-Transformer model for Bengali Sign Language interpretation
This study introduces a novel hybrid CNN-Transformer architecture to address the limited progress in Bengali SLR, focusing on isolated sign word recognition and sentence generation. This specific model combination is new to Bengali SLR tasks. A custom video dataset was developed, featuring 62 distin
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Nepali Sign Language Characters Recognition: Dataset Development and Deep Learning Approaches#1061635
- Classification of Sign-language Using VGG16#98024
- SMART: MLLM-guided Temporal Alignment for Unifying Sign Language Recognition and Spotting#799092
- SMART: MLLM-guided Temporal Alignment for Unifying Sign Language Recognition and Spotting#797669
- SEA-SpeechBench: A Large-Scale Multitask Benchmark for Speech Understanding Across Southeast Asia#988004
Record · ID 1061991
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive