de-kerneled corn
去芯玉米
being de-kerneled
正在去芯
de-kerneled product
去芯产品
fully de-kerneled
完全去芯
de-kerneled kernels
去芯粒
de-kerneled quickly
快速去芯
de-kerneled sample
去芯样品
de-kerneled state
去芯状态
de-kerneled batch
去芯批次
de-kerneled efficiently
高效去芯
the de-kerneled data revealed a surprising pattern in user behavior.
去核的数据揭示了用户行为中令人惊讶的模式。
we used de-kerneled images to improve the accuracy of our model.
我们使用去核图像来提高我们模型的准确性。
de-kerneled signals allowed for a clearer analysis of the noise.
去核信号使噪声分析更加清晰。
the de-kerneled network demonstrated improved performance on the test set.
去核网络在测试集上表现出更好的性能。
after de-kerneling, the data was easier to process and analyze.
去核后，数据更容易处理和分析。
the researchers opted to de-kernel the data before feature extraction.
研究人员选择在特征提取之前对数据进行去核处理。
de-kerneled features significantly reduced the dimensionality of the dataset.
去核特征显著减少了数据集的维度。
we compared the results of the de-kerneled and non-de-kerneled approaches.
我们比较了去核方法和非去核方法的实验结果。
the de-kerneled representation captured subtle nuances in the data.
去核表示捕捉了数据中的微妙细微差别。
de-kerneled audio signals were used for speech recognition tasks.
去核音频信号用于语音识别任务。
the process of de-kerneling the data was computationally intensive.
对数据进行去核处理的过程计算量很大。
de-kerneled corn
去芯玉米
being de-kerneled
正在去芯
de-kerneled product
去芯产品
fully de-kerneled
完全去芯
de-kerneled kernels
去芯粒
de-kerneled quickly
快速去芯
de-kerneled sample
去芯样品
de-kerneled state
去芯状态
de-kerneled batch
去芯批次
de-kerneled efficiently
高效去芯
the de-kerneled data revealed a surprising pattern in user behavior.
去核的数据揭示了用户行为中令人惊讶的模式。
we used de-kerneled images to improve the accuracy of our model.
我们使用去核图像来提高我们模型的准确性。
de-kerneled signals allowed for a clearer analysis of the noise.
去核信号使噪声分析更加清晰。
the de-kerneled network demonstrated improved performance on the test set.
去核网络在测试集上表现出更好的性能。
after de-kerneling, the data was easier to process and analyze.
去核后，数据更容易处理和分析。
the researchers opted to de-kernel the data before feature extraction.
研究人员选择在特征提取之前对数据进行去核处理。
de-kerneled features significantly reduced the dimensionality of the dataset.
去核特征显著减少了数据集的维度。
we compared the results of the de-kerneled and non-de-kerneled approaches.
我们比较了去核方法和非去核方法的实验结果。
the de-kerneled representation captured subtle nuances in the data.
去核表示捕捉了数据中的微妙细微差别。
de-kerneled audio signals were used for speech recognition tasks.
去核音频信号用于语音识别任务。
the process of de-kerneling the data was computationally intensive.
对数据进行去核处理的过程计算量很大。
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