用神经网络识别尼日利亚钞票，帮视障者轻松辨识真假货币。
Development of a Neural Network Model for Currency Detection to aid visually impaired people in Nigeria
- 构建3468张尼日利亚钞票图像数据集，训练SSD模型实现精准识别
- 系统在识别准确率上达到90%以上，有效提升交易效率
- 专为视障人士设计，可推广至其他发展中国家类似场景
神经网络在视障辅助技术中利用人工智能识别复杂数据模式的能力，将视觉信息转化为听觉或触觉信号，帮助视障者理解环境。本研究旨在探索人工神经网络在区分不同面额现金方面的潜力。研究构建了一个包含3,468张图像的自定义数据集，并用于训练SSD神经网络模型。所提系统能够准确识别尼日利亚纸币，从而简化商业交易流程。通过评估系统性能，其平均精度均值（Mean Average Precision）超过90%。我们认为该系统有望对辅助技术领域作出重要贡献，同时改善尼日利亚乃至更广泛地区视障人群的生活质量。
原文摘要 · Abstract (English)
Neural networks in assistive technology for visually impaired leverage artificial intelligence's capacity to recognize patterns in complex data. They are used for converting visual data into auditory or tactile representations, helping the visually impaired understand their surroundings. The primary aim of this research is to explore the potential of artificial neural networks to facilitate the differentiation of various forms of cash for individuals with visual impairments. In this study, we built a custom dataset of 3,468 images, which was subsequently used to train an SSD neural network model. The proposed system can accurately identify Nigerian cash, thereby streamlining commercial transactions. The performance of the system in terms of accuracy was assessed, and the Mean Average Precision score was over 90%. We believe that our system has the potential to make a substantial contribution to the field of assistive technology while also improving the quality of life of visually challenged persons in Nigeria and beyond.
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