{"id":31349,"date":"2024-10-28T12:01:23","date_gmt":"2024-10-28T12:01:23","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=31349"},"modified":"2024-11-26T06:45:26","modified_gmt":"2024-11-26T06:45:26","slug":"%eb%94%a5%eb%9f%ac%eb%8b%9d%ea%b3%bc-%eb%a8%b8%ec%8b%a0%eb%9f%ac%eb%8b%9d%ec%9d%84-%ed%99%9c%ec%9a%a9%ed%95%9c-%ec%9e%90%eb%8f%99%eb%a7%a4%eb%a7%a4-cnn%ec%9d%84-%ec%82%ac%ec%9a%a9%ed%95%9c-%ed%8c%a8","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/31349\/","title":{"rendered":"\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815."},"content":{"rendered":"

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CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5<\/h2>\n

\uc554\ud638\ud654\ud3d0\uc758 \uae09\uaca9\ud55c \uac00\uaca9 \ubcc0\ub3d9\uc131\uacfc \ub192\uc740 \uac70\ub798\ub7c9 \ub355\ubd84\uc5d0 \ube44\ud2b8\ucf54\uc778 \uac70\ub798\ub294 \ub9ce\uc740 \ud22c\uc790\uc790\uc640 \ub9e4\ub9e4 \uc54c\uace0\ub9ac\uc998\uc5d0\uac8c \ub9e4\ub825\uc801\uc778 \uc2dc\uc7a5\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \uacfc\uac70 \uac00\uaca9 \ud328\ud134\uc744 \ubd84\uc11d\ud558\uace0, \ubbf8\ub798 \uac00\uaca9 \ubcc0\ub3d9\uc744 \uc608\uce21\ud558\ub294 \uc54c\uace0\ub9ac\uc998 \uac70\ub798 \uc804\ub7b5\uc774 \uc8fc\ubaa9\ubc1b\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Convolutional Neural Networks (CNN)\ub97c \uc774\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18\uc758 \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc124\uba85\ud558\uace0, \uc2e4\uc6a9\uc801\uc778 \uc608\uc81c \ucf54\ub4dc\ub97c \ud1b5\ud574 \uc774\ub97c \uad6c\ud604\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n

1. CNN\uacfc \ub525\ub7ec\ub2dd\uc758 \uc774\ud574<\/h3>\n

Convolutional Neural Networks (CNN)\uc740 \uc774\ubbf8\uc9c0 \uc778\uc2dd \ubc0f \ube44\uc804 \uad00\ub828 \uc791\uc5c5\uc5d0 \ud0c1\uc6d4\ud55c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc8fc\ub294 \ub525\ub7ec\ub2dd \uc544\ud0a4\ud14d\ucc98\uc785\ub2c8\ub2e4. CNN\uc740 \ub3d9\uc77c\ud55c \uac00\uc911\uce58\ub97c \uc0ac\uc6a9\ud558\ub294 \ud544\ud130(\ub610\ub294 \ucee4\ub110)\ub97c \ud1b5\ud574 \uc5ec\ub7ec \uc774\ubbf8\uc9c0\ub97c \ubd84\uc11d\ud558\uc5ec \uc911\uc694\ud55c \ud2b9\uc9d5(feature)\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud558\uace0, \uc774\ub97c \ud1b5\ud55c \ub9e4\ub9e4 \uacb0\uc815\uc744 \uc9c0\uc6d0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

2. \ube44\ud2b8\ucf54\uc778 \ub9e4\ub9e4\uc5d0\uc11c\uc758 \ub525\ub7ec\ub2dd \uc0ac\uc6a9 \uc0ac\ub840<\/h3>\n

\ub525\ub7ec\ub2dd\uc740 \ube44\ud2b8\ucf54\uc778 \uac70\ub798\uc5d0\uc11c \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc608\uce21\uc5d0 \uc720\uc6a9\ud558\uac8c \uc0ac\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130\uc758 \uc790\ub3d9 \ud0d0\uc0c9, \ud328\ud134 \uc778\uc2dd \ubc0f \uc608\uce21 \uc54c\uace0\ub9ac\uc998\uc744 \ud1b5\ud574 \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4. CNN\uc740 \ube44\ud2b8\ucf54\uc778 \uac00\uaca9 \ubcc0\ub3d9\uc758 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130(\uc608: 1\uc2dc\uac04\ub9c8\ub2e4 \uae30\ub85d\ub41c \uc2dc\uc138)\ub97c \uc774\ubbf8\uc9c0\ub85c \ubcc0\ud658\ud55c \ud6c4, \uc774\ub97c \ud1b5\ud574 \ud559\uc2b5\ud569\ub2c8\ub2e4.<\/p>\n

2.1 \ub370\uc774\ud130 \uc218\uc9d1<\/h4>\n

\ube44\ud2b8\ucf54\uc778 \uac00\uaca9 \ub370\uc774\ud130\ub294 \uc5ec\ub7ec \uacf5\uac1c API\ub97c \ud1b5\ud574 \uc218\uc9d1\ud560 \uc218 \uc788\uc73c\uba70, \uadf8 \uc911\uc5d0\uc11c\ub3c4 Binance API<\/a>\uac00 \ub9ce\uc774 \ud65c\uc6a9\ub429\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc81c\ub294 Python\uc744 \uc0ac\uc6a9\ud558\uc5ec Binance API\uc5d0\uc11c \ube44\ud2b8\ucf54\uc778 \uac00\uaca9 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/p>\n

import requests\nimport pandas as pd\nimport datetime\n\ndef fetch_binance_data(symbol='BTCUSDT', interval='1h', limit=1000):\n    url = f'https:\/\/api.binance.com\/api\/v3\/klines?symbol={symbol}&interval={interval}&limit={limit}'\n    response = requests.get(url)\n    data = response.json()\n\n    df = pd.DataFrame(data, columns=['open_time', 'open', 'high', 'low', 'close', 'volume', \n                                      'close_time', 'quote_asset_volume', 'number_of_trades', \n                                      'taker_buy_volume', 'taker_buy_quote_asset_volume', 'ignore'])\n    df['open_time'] = pd.to_datetime(df['open_time'], unit='ms')\n    df['close'] = df['close'].astype(float)\n    \n    return df[['open_time', 'close']]\n\nbtc_data = fetch_binance_data()\nprint(btc_data.head())<\/code><\/pre>\n
2.2 \ub370\uc774\ud130 \uc804\ucc98\ub9ac \ubc0f \uc774\ubbf8\uc9c0 \uc0dd\uc131<\/h4>\n
\uc218\uc9d1\ud55c \uac00\uaca9 \ub370\uc774\ud130\ub97c \ub370\uc774\ud130 \uc804\ucc98\ub9ac \uacfc\uc815\uc744 \ud1b5\ud574 CNN\uc5d0 \uc801\ud569\ud55c \ud615\ud0dc\ub85c \ubcc0\ud658\ud574\uc57c \ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc774\ub3d9 \ud3c9\uade0\uc774\ub098 \ubcfc\ub9b0\uc800 \ubc34\ub4dc\uc640 \uac19\uc740 \uae30\uc220\uc801 \uc9c0\ud45c\ub97c \uacc4\uc0b0\ud558\uc5ec \ucd94\uac00\uc801\uc778 \ud53c\ucc98\ub97c \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \ud6c4, \ubcc0\ud658\ub41c \ub370\uc774\ud130\ub97c \ucc28\ud2b8\ub85c \ub9cc\ub4e4\uc5b4 \uc774\ubbf8\uc9c0 \ud30c\uc77c\ub85c \uc800\uc7a5\ud558\ub294 \ubc29\uc2dd\uc73c\ub85c CNN\uc758 \uc785\ub825 \ub370\uc774\ud130\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
import matplotlib.pyplot as plt\nimport numpy as np\n\ndef plot_price_chart(data):\n    plt.figure(figsize=(10, 5))\n    plt.plot(data['open_time'], data['close'], label='Close Price', color='blue')\n    plt.title('Bitcoin Price Chart')\n    plt.xlabel('Time')\n    plt.ylabel('Price (USDT)')\n    plt.legend()\n    plt.grid()\n    plt.savefig('btc_price_chart.png')\n    plt.close()\n\nplot_price_chart(btc_data)<\/code><\/pre>\n
3. CNN \ubaa8\ub378 \uad6c\ucd95 \ubc0f \ud559\uc2b5<\/h3>\n
\uc774\uc81c \ub370\uc774\ud130\ub97c CNN \ubaa8\ub378\uc5d0 \uc785\ub825\ud560 \uc218 \uc788\ub3c4\ub85d \uad6c\uc131\ud574\uc57c \ud569\ub2c8\ub2e4. TensorFlow\/Keras \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec CNN \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uace0 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
from tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\n\n# CNN \ubaa8\ub378 \uc815\uc758\ndef create_cnn_model():\n    model = Sequential()\n\n    model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(64, 64, 3)))\n    model.add(MaxPooling2D(pool_size=(2, 2)))\n    model.add(Conv2D(64, kernel_size=(3, 3), activation='relu'))\n    model.add(MaxPooling2D(pool_size=(2, 2)))\n    model.add(Flatten())\n    model.add(Dense(128, activation='relu'))\n    model.add(Dense(2, activation='softmax'))  # \ub450 \uac1c\uc758 \ud074\ub798\uc2a4\ub97c \ubd84\ub958 (Buy\/Sell)\n\n    model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])\n    return model\n\ncnn_model = create_cnn_model()\ncnn_model.summary()<\/code><\/pre>\n
3.1 \ubaa8\ub378 \ud559\uc2b5<\/h4>\n
\uc774\ubbf8\uc9c0\ub97c \ud559\uc2b5\ud558\uae30 \uc704\ud574 ImageDataGenerator\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130 \uc99d\uac15\uc744 \uc218\ud589\ud558\uace0, \ubaa8\ub378\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
from sklearn.model_selection import train_test_split\nfrom tensorflow.keras.utils import to_categorical\n\n# \uc774\ubbf8\uc9c0 \ub370\uc774\ud130\ub97c \uac00\uc838\uc624\ub294 \uc0ac\uc6a9\uc790 \uc815\uc758 \ud568\uc218 (\uac00\uc815)\ndef load_images_and_labels():\n    # \uc774\ubbf8\uc9c0\uc640 \ub77c\ubca8\uc744 \ub85c\ub4dc\ud558\ub294 \ub17c\ub9ac \uad6c\ud604\n    return images, labels\n\nimages, labels = load_images_and_labels()\nX_train, X_test, y_train, y_test = train_test_split(images, labels, test_size=0.2)\n\n# \ub77c\ubca8\uc744 one-hot \uc778\ucf54\ub529\ny_train = to_categorical(y_train, num_classes=2)\ny_test = to_categorical(y_test, num_classes=2)\n\n# \ub370\uc774\ud130 \uc99d\uac15 \uc124\uc815\ndatagen = ImageDataGenerator(\n    rotation_range=10,\n    width_shift_range=0.1,\n    height_shift_range=0.1,\n    shear_range=0.1,\n    zoom_range=0.1,\n    horizontal_flip=True,\n    fill_mode='nearest')\n\n# \ubaa8\ub378 \ud559\uc2b5\ncnn_model.fit(datagen.flow(X_train, y_train, batch_size=32), \n               validation_data=(X_test, y_test), \n               epochs=50) <\/code><\/pre>\n
4. \ub9e4\ub9e4 \uacb0\uc815 \ubc0f \uc804\ub7b5 \uad6c\ud604<\/h3>\n
\ubaa8\ub378\uc774 \ud559\uc2b5\uc744 \ub9c8\uce58\uba74, \uc774\ub97c \ud1b5\ud574 \ube44\ud2b8\ucf54\uc778 \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \uc804\ub7b5\uc744 \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc0c8\ub85c\uc6b4 \ub370\uc774\ud130\uc5d0 \ub300\ud574 \uc608\uce21\uc744 \uc218\ud589\ud558\uace0, \ud2b9\uc815 \uc784\uacc4\uac12 \uc774\uc0c1\uc774\uac70\ub098 \uc774\ud558\uc77c \uacbd\uc6b0 \ub9e4\uc218 \ub610\ub294 \ub9e4\ub3c4 \uc2e0\ud638\ub97c \uc0dd\uc131\ud558\ub3c4\ub85d \uc124\uc815\ud569\ub2c8\ub2e4.<\/p>\n
def make_trade_decision(image):\n    # \uc774\ubbf8\uc9c0\ub97c CNN\uc758 \uc785\ub825 \ud615\ud0dc\ub85c \ubcc0\ud658\n    processed_image = preprocess_image(image)\n    prediction = cnn_model.predict(np.expand_dims(processed_image, axis=0))\n\n    return 'Buy' if prediction[0][0] > 0.5 else 'Sell'\n\nlatest_chart_image = 'latest_btc_price_chart.png'\ndecision = make_trade_decision(latest_chart_image)\nprint(f'Trade Decision: {decision}') <\/code><\/pre>\n
5. \uacb0\ub860<\/h3>\n
\uc774\ubc88 \uac15\uc88c\uc5d0\uc11c\ub294 \ub525\ub7ec\ub2dd \ubc0f CNN\uc744 \ud65c\uc6a9\ud558\uc5ec \ube44\ud2b8\ucf54\uc778 \uc790\ub3d9\ub9e4\ub9e4 \uc804\ub7b5\uc744 \uad6c\ud604\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130 \uc218\uc9d1, \uc804\ucc98\ub9ac \ubc0f \uc774\ubbf8\uc9c0 \uc0dd\uc131, CNN \ubaa8\ub378 \uad6c\ucd95 \ubc0f \ud559\uc2b5, \uadf8\ub9ac\uace0 \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \uad6c\uc870\ub97c \ud1b5\ud574 \uae30\uacc4 \ud559\uc2b5\uc744 \uac70\ub798\uc5d0 \uc801\uc6a9\ud558\ub294 \ud504\ub85c\uc138\uc2a4\ub97c \uc2e4\ud589\uc5d0 \uc62e\uae38 \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc740 \uc2e4\uc81c\ub85c \ub2e4\uc591\ud55c \ub370\uc774\ud130\uc640 \uae30\uc220\uc801 \uc9c0\ud45c\ub97c \uacb0\ud569\ud558\uc5ec \ub354 \uc815\uad50\ud55c \uc804\ub7b5\uc73c\ub85c \ubc1c\uc804\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\ub9c8\uc9c0\ub9c9\uc73c\ub85c, \ube44\ud2b8\ucf54\uc778 \uac70\ub798\uc5d0\uc11c \ud56d\uc0c1 \ub9ac\uc2a4\ud06c\uac00 \uc874\uc7ac\ud558\uba70, \ubaa8\ub378\uc774 \uc608\uce21\ud558\ub294 \uacb0\uacfc\ub294 \uacfc\uac70 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ud55c \uac83\uc774\ubbc0\ub85c \uc2e0\uc911\ud55c \uc811\uadfc\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n<\/article>\n
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CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \uc554\ud638\ud654\ud3d0\uc758 \uae09\uaca9\ud55c \uac00\uaca9 \ubcc0\ub3d9\uc131\uacfc \ub192\uc740 \uac70\ub798\ub7c9 \ub355\ubd84\uc5d0 \ube44\ud2b8\ucf54\uc778 \uac70\ub798\ub294 \ub9ce\uc740 \ud22c\uc790\uc790\uc640 \ub9e4\ub9e4 \uc54c\uace0\ub9ac\uc998\uc5d0\uac8c \ub9e4\ub825\uc801\uc778 \uc2dc\uc7a5\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \uacfc\uac70 \uac00\uaca9 \ud328\ud134\uc744 \ubd84\uc11d\ud558\uace0, \ubbf8\ub798 \uac00\uaca9 \ubcc0\ub3d9\uc744 \uc608\uce21\ud558\ub294 \uc54c\uace0\ub9ac\uc998 \uac70\ub798 \uc804\ub7b5\uc774 \uc8fc\ubaa9\ubc1b\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Convolutional Neural Networks (CNN)\ub97c \uc774\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18\uc758 \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc124\uba85\ud558\uace0, … \ub354 \ubcf4\uae30 “\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5  \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815.”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[29],"tags":[],"class_list":["post-31349","post","type-post","status-publish","format-standard","hentry","category-29"],"yoast_head":"\n\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815. - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/31349\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815. - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \uc554\ud638\ud654\ud3d0\uc758 \uae09\uaca9\ud55c \uac00\uaca9 \ubcc0\ub3d9\uc131\uacfc \ub192\uc740 \uac70\ub798\ub7c9 \ub355\ubd84\uc5d0 \ube44\ud2b8\ucf54\uc778 \uac70\ub798\ub294 \ub9ce\uc740 \ud22c\uc790\uc790\uc640 \ub9e4\ub9e4 \uc54c\uace0\ub9ac\uc998\uc5d0\uac8c \ub9e4\ub825\uc801\uc778 \uc2dc\uc7a5\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \uacfc\uac70 \uac00\uaca9 \ud328\ud134\uc744 \ubd84\uc11d\ud558\uace0, \ubbf8\ub798 \uac00\uaca9 \ubcc0\ub3d9\uc744 \uc608\uce21\ud558\ub294 \uc54c\uace0\ub9ac\uc998 \uac70\ub798 \uc804\ub7b5\uc774 \uc8fc\ubaa9\ubc1b\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 Convolutional Neural Networks (CNN)\ub97c \uc774\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18\uc758 \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc124\uba85\ud558\uace0, … \ub354 \ubcf4\uae30 "\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815."\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/31349\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-10-28T12:01:23+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:45:26+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:site\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"root\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"2\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/atmokpo.com\/w\/31349\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/atmokpo.com\/w\/31349\/\"},\"author\":{\"name\":\"root\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\"},\"headline\":\"\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815.\",\"datePublished\":\"2024-10-28T12:01:23+00:00\",\"dateModified\":\"2024-11-26T06:45:26+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/atmokpo.com\/w\/31349\/\"},\"wordCount\":30,\"publisher\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\"},\"articleSection\":[\"\ub525\ub7ec\ub2dd \uba38\uc2e0\ub7ec\ub2dd \uc790\ub3d9 \ud2b8\ub808\uc774\ub529\"],\"inLanguage\":\"ko-KR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/atmokpo.com\/w\/31349\/\",\"url\":\"https:\/\/atmokpo.com\/w\/31349\/\",\"name\":\"\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, CNN\uc744 \uc0ac\uc6a9\ud55c \ud328\ud134 \uc778\uc2dd \uae30\ubc18 \ub9e4\ub9e4 \uc804\ub7b5 \ucc28\ud2b8 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud574 \ub9e4\ub9e4 \uacb0\uc815. - 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