anonymous-submission-hf/tactile-mnist-touch-syn-single-t32-64x64
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合成触觉MNIST数据集是一个图像分类数据集，专为触觉传感设计。它基于MNIST手写数字数据集，通过GelSight Mini传感器模拟触觉感知，生成合成触觉图像。每轮数据包含32次触摸，图像分辨率为64x64像素，适用于训练和评估触觉图像分类模型。数据集支持触觉传感和分类任务，可用于研究触觉感知与计算机视觉的结合。
The Synthetic Tactile MNIST Dataset is an image classification dataset designed for tactile sensing. It is based on the MNIST handwritten digits dataset and simulates tactile perception using the GelSight Mini sensor to generate synthetic tactile images. Each round of data includes 32 touches, with images at a resolution of 64x64 pixels, suitable for training and evaluating tactile image classification models. The dataset supports tactile sensing and classification tasks, enabling research on the integration of tactile perception and computer vision.
