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莊于霆 Tim
中文數字手寫辨識
中文數字手寫辨識
中文數字手寫辨識
By
莊于霆 Tim
・
Taipei, Taiwan
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課堂上全班合力蒐集約一萬八千份的中文數字(一 ~ 十)手寫圖片資料。在將收集到的手寫資料預處理後, 將其轉為 28 x 28 的圖片大小,再利用 Keras 實現 CNN 卷積式類神經網路進行深度學習。 CNN 模組由兩層卷積層兩層池化層組成, 最後由softmax來進行分類。而訓練與測試資料的分配,其中的一萬六千份資料作為訓練資料,兩千份做為測試資料, 最後模型訓練結果準確度達到九成。 本專案是我首次接觸到人工智慧的技術與 Python 語言的應用, 了解資料預處理與優化對於深度學習準確度的重要性。。此專案在使用 CNN 之前, 也有使用無卷積池化的單純 MLP 多層感知機的實作,但結果準確度相對較差。
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莊于霆 Tim
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Published: Mar 21st 2020
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