A corpus of 10,000 Bangla sentences, manually annotated into four functional categories, namely declarative, interrogative, imperative, and exclamatory is introduced, and Experimental results show that TF-IDF consistently outperforms Word2Vec, likely due to its ability to emphasize discriminative lexical cues associate...
Swapnil Kundu Argha, Abdullah Al Shafi, Rowzatul Zannat et al.· 0 citations
A comprehensive methodological comparison of three influential frameworks, namely Multimodal Adaptive Extraction, Solar, and UniMMQA, tracing the evolution of multimodal question answering from modality-adaptive pipelines to fully unified architectures reveals a clear shift from explicit modality-specific processing to...
Experimental evaluation on two public retinal fundus datasets demonstrates that deep feature-based methods consistently outperform handcrafted feature-based methods, while the proposed attention-enhanced framework achieves the best overall performance.
Abdullah Al Shafi, Nishat Sadaf Lira, A. Hasan et al.· 0 citations
BanglaMed-QA, a robust QA system specifically designed for the Bangla medical domain, is introduced and supervised machine learning models in which SVM is found to be the best model to categorize questions are adopted.
Rowzatul Zannat, Abdullah Al Shafi, K. M. Azharul Hasan et al.· 0 citations
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