de-kerneled corn
去籽玉米
being de-kerneled
正在去籽
de-kerneled product
去籽產品
fully de-kerneled
完全去籽
de-kerneled kernels
去籽玉米粒
de-kerneled quickly
快速去籽
de-kerneled sample
去籽樣本
de-kerneled state
去籽狀態
de-kerneled batch
去籽批次
de-kerneled efficiently
高效去籽
the de-kerneled data revealed a surprising pattern in user behavior.
去核的數據揭示了用戶行為中令人驚訝的模式。
we used de-kerneled images to improve the accuracy of our model.
我們使用去核的圖像來提高模型的準確性。
de-kerneled signals allowed for a clearer analysis of the noise.
去核的信號允許對雜訊進行更清晰的分析。
the de-kerneled network demonstrated improved performance on the test set.
去核的網絡在測試集上表現出改進的性能。
after de-kerneling, the data was easier to process and analyze.
去核後，數據更容易處理和分析。
the researchers opted to de-kernel the data before feature extraction.
研究人員選擇在特徵提取之前對數據進行去核。
de-kerneled features significantly reduced the dimensionality of the dataset.
去核的特徵顯著降低了數據集的維度。
we compared the results of the de-kerneled and non-de-kerneled approaches.
我們比較了去核和未去核方法的結果。
the de-kerneled representation captured subtle nuances in the data.
去核的表示方式捕捉了數據中的細微差異。
de-kerneled audio signals were used for speech recognition tasks.
去核的音訊信號用於語音識別任務。
the process of de-kerneling the data was computationally intensive.
對數據進行去核的過程計算量很大。
de-kerneled corn
去籽玉米
being de-kerneled
正在去籽
de-kerneled product
去籽產品
fully de-kerneled
完全去籽
de-kerneled kernels
去籽玉米粒
de-kerneled quickly
快速去籽
de-kerneled sample
去籽樣本
de-kerneled state
去籽狀態
de-kerneled batch
去籽批次
de-kerneled efficiently
高效去籽
the de-kerneled data revealed a surprising pattern in user behavior.
去核的數據揭示了用戶行為中令人驚訝的模式。
we used de-kerneled images to improve the accuracy of our model.
我們使用去核的圖像來提高模型的準確性。
de-kerneled signals allowed for a clearer analysis of the noise.
去核的信號允許對雜訊進行更清晰的分析。
the de-kerneled network demonstrated improved performance on the test set.
去核的網絡在測試集上表現出改進的性能。
after de-kerneling, the data was easier to process and analyze.
去核後，數據更容易處理和分析。
the researchers opted to de-kernel the data before feature extraction.
研究人員選擇在特徵提取之前對數據進行去核。
de-kerneled features significantly reduced the dimensionality of the dataset.
去核的特徵顯著降低了數據集的維度。
we compared the results of the de-kerneled and non-de-kerneled approaches.
我們比較了去核和未去核方法的結果。
the de-kerneled representation captured subtle nuances in the data.
去核的表示方式捕捉了數據中的細微差異。
de-kerneled audio signals were used for speech recognition tasks.
去核的音訊信號用於語音識別任務。
the process of de-kerneling the data was computationally intensive.
對數據進行去核的過程計算量很大。
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