报告详情
Leveraging Gemini 1.5 Pro and Prompt Engineering for Robust Handwriting Interpretation
编号：191
访问权限：仅限参会人
更新：2025-12-23 13:40:13 浏览：25次
拓展类型2
摘要
Malayalam handwritten script recognition is a challenging task due to the language's complex script and diverse writing styles. Recent advancements in deep learning and prompt engineering offer promising solutions to improve recognition accuracy. This study explores the application of prompt engineering techniques to enhance the performance of Malayalam handwritten script recognition models. By designing effective prompts, we aim to leverage the capabilities of pre-trained language models and improve their ability to recognize handwritten Malayalam text. Our approach involves crafting prompts that capture the nuances of the Malayalam script and utilizing them to fine-tune pre-trained models. We evaluate the performance of our approach on a dataset of Malayalam handwritten text and demonstrate significant improvements in recognition accuracy. Our findings highlight the potential of prompt engineering in improving the performance of handwritten script recognition models for languages like Malayalam.
关键词
Prompt Engineering, Malayalam Handwritten Script Recognition, Deep Learning, Pre-trained Language Models.
报告人
Gargy G
research scholar NICHE稿件作者
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重要日期
-
会议日期
12月29日
2025
至12月31日
2025
-
12月30日 2025
报告提交截止日期
-
12月30日 2025
注册截止日期
-
12月31日 2025
初稿截稿日期
主办单位
国际科学联合会
承办单位
扎尔卡大学
联系方式
- Miss AsianComNet
- as******@usssociety.org
历届会议
-
2024年10月24日 泰国 Bangkok
2024亚洲通讯与网络会议
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