利用单卤化物过氧化物光伏电池实现人机交互的动态手势识别算法

2024 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2024-01-28 DOI:10.1109/ICEIC61013.2024.10457182

An Kyung-Chan, Jun-Ying Li, Chu-Feng Yang, Ng Si En Timothy, Shibi Varku, Qinjie Wu, Priyanka Kajal, N. Mathews, Arindam Basu, Tony Tae-Hyoung Kim

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引用次数: 0

摘要

本作品介绍了一种用于单个光伏电池的手势识别系统，并对几种手势识别算法进行了比较和深入分析。基于卤化物磷酸盐的光伏电池被用作手势识别的单一传感器。在对不同算法进行测试和比较后，选择了多层感知器（MLP）分类算法来识别光伏电池的手势。通过使用所提出的 MLP 分类算法，我们所提出的手势识别系统在所收集的数据集上的准确率达到了 100%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Dynamic Gesture Recognition Algorithm Using Single Halide Perovskite Photovoltaic Cell for Human-Machine Interaction

This work presents a hand gesture recognition system for a single photovoltaic(PV) cell and provides a comparison and insight into several gesture recognition algorithms. The photovoltaic cell based on halide perovskites is used for a single sensor for hand gesture recognition. The multi-layer perceptron(MLP) classification algorithm was selected to recognize hand gestures from a PV cell after testing and comparing different algorithms. Using the proposed MLP classification algorithm, our proposed hand-gesture recognition system can provide 100% accuracy on our collected dataset.

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来源期刊

2024 International Conference on Electronics, Information, and Communication (ICEIC)

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