Year: 2025
Type: article
Abstract: Image captioning has gained significant attention, with most of the research efforts directed toward the English language. While some work has been explored in regional languages such as Hindi and Bengali, Nepali remains largely underrepresented in this domain. Furthermore, publicly accessible Nepali-language datasets for image captioning are extremely limited. This study leverages an existing pre-trained dataset that includes Nepali image captions and employs deep learning methods to automatically generate descriptions in the Nepali language. The architecture used integrates a Convolutional Neural Network (CNN) for image understanding and a Transformer model for sequence generation. In our approach, EfficientNetB0, a pre-trained CNN model, is utilized to extract high-level features from images. These features are then fed into the Transformer, which generates the corresponding captions in Nepali. The experimental results demonstrate encouraging performance, suggesting the approach is effective and holds potential for further refinement in future research.
Authors: Swarup Singh Tharu, Savin Basnet, Arun Thapa, Prashant Poudel
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414613747
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