P‐43: Development of 3D Crosstalk Classification Model Using Deep Learning†

Young-sang Ha, R. Mok, Beom-shik Kim
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Abstract

We propose development of a 3D X‐Talk classification model using deep learning. Secure X‐Talk image data of various LFD products and classify images for each feature. After image labeling and feasibility evaluation to utilize the deep learning model as a learning image, the performance of the model was improved and the platform was developed. This requires a faster and more accurate classification model to classify X‐Talk levels in the quality inspection process for commercial LFD product production.
P‐43:基于深度学习的三维相声分类模型的开发[j]
我们建议使用深度学习开发3D X - Talk分类模型。保护各种LFD产品的X - Talk图像数据,并对每个特征的图像进行分类。经过图像标注和可行性评估,将深度学习模型作为学习图像,改进模型性能,开发平台。这需要一个更快、更准确的分类模型来对商用LFD产品生产的质量检测过程中的X‐Talk级别进行分类。
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