\ub9ac\uc5bc\ud55c \ub370\uc774\ud130 \uc0dd\uc131: GAN\uc758 \ub6f0\uc5b4\ub09c \uc0dd\uc131 \ub2a5\ub825\uc73c\ub85c \uc778\ud574 \uc2e4\uc81c\uc640 \uc720\uc0ac\ud55c \ub370\uc774\ud130\ub97c \ub9cc\ub4e4\uc5b4 \ub0bc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n4.1 GAN\uc744 \uc774\uc6a9\ud55c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131 \uad6c\ud604<\/h3>\n
\ud569\uc131 \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud558\uae30 \uc704\ud574 GAN\uc744 \uad6c\ud604\ud558\ub294 \uae30\ubcf8\uc801\uc778 \ucf54\ub4dc\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\nfrom tensorflow.keras import layers\n\n# GAN \ubaa8\ub378 \uc0dd\uc131 \ud568\uc218\ndef create_gan():\n # \uc0dd\uc131\uc790 \ubaa8\ub378 \uc815\uc758\n generator = tf.keras.Sequential([\n layers.Dense(128, activation='relu', input_shape=(100,)),\n layers.Dense(784, activation='sigmoid')\n ])\n\n # \ud310\ubcc4\uc790 \ubaa8\ub378 \uc815\uc758\n discriminator = tf.keras.Sequential([\n layers.Dense(128, activation='relu', input_shape=(784,)),\n layers.Dense(1, activation='sigmoid')\n ])\n\n # GAN \ubaa8\ub378 \uc815\uc758\n discriminator.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n discriminator.trainable = False\n gan_input = layers.Input(shape=(100,))\n fake_image = generator(gan_input)\n gan_output = discriminator(fake_image)\n gan = tf.keras.models.Model(gan_input, gan_output)\n gan.compile(loss='binary_crossentropy', optimizer='adam')\n\n return generator, discriminator, gan\n\n# \ub370\uc774\ud130 \uc0dd\uc131 \ubc0f \ubaa8\ub378 \ud6c8\ub828\ngenerator, discriminator, gan = create_gan()\n\nfor epoch in range(10000):\n # \uae30\uc874 \ub370\uc774\ud130\ub85c\ubd80\ud130 \uc9c4\uc9dc \uc0d8\ud50c \uc0dd\uc131\n real_samples = np.random.rand(32, 784)\n \n # \uac00\uc9dc \ub370\uc774\ud130 \uc0dd\uc131\n noise = np.random.normal(0, 1, size=[32, 100])\n fake_samples = generator.predict(noise)\n \n # \ud310\ubcc4\uc790 \ud6c8\ub828\n discriminator.train_on_batch(real_samples, np.ones((32, 1)))\n discriminator.train_on_batch(fake_samples, np.zeros((32, 1)))\n \n # GAN \ud6c8\ub828\n noise = np.random.normal(0, 1, size=[32, 100])\n gan.train_on_batch(noise, np.ones((32, 1)))\n \n# \ub370\uc774\ud130 \uc0dd\uc131 \ud6c4 \uc2dc\uac01\ud654\ngenerated_images = generator.predict(np.random.normal(0, 1, size=[10, 100]))\nplt.figure(figsize=(10, 10))\nfor i in range(10):\n plt.subplot(5, 5, i + 1)\n plt.imshow(generated_images[i].reshape(28, 28), cmap='gray')\n plt.axis('off')\nplt.show()\n <\/code><\/pre>\n5. \uacb0\ub860<\/h2>\n
\uc774 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uac1c\ub150\uacfc GAN\uc744 \ud65c\uc6a9\ud55c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131 \uae30\uc220\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \ucd94\ucd9c\ud558\uace0 \ud569\uc131 \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud558\ub294 \ub2a5\ub825\uc740 \ud000\ud2b8 \ud2b8\ub808\uc774\ub529 \uc2dc\uc2a4\ud15c\uc744 \uac1c\uc120\ud558\ub294 \uac15\ub825\ud55c \ub3c4\uad6c\uac00 \ub420 \uac83\uc785\ub2c8\ub2e4. \ubbf8\ub798\uc758 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc95\uc744 \uc131\uacf5\uc801\uc73c\ub85c \uc801\uc6a9\ud558\uae30 \uc704\ud574 \uccb4\uacc4\uc801\uc778 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc54c\uace0\ub9ac\uc998 \uad6c\ucd95\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\ud000\ud2b8 \ud2b8\ub808\uc774\ub529\uc740 \ub370\uc774\ud130 \uae30\ubc18\uc73c\ub85c \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \uac70\ub798 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. \ub2e4\uc591\ud55c \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \ucc3e\uc544\ub0b4\uace0, \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc790\ub3d9 \ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uace0, Generative Adversarial Networks (GAN)\uc744 \ud1b5\ud574 \ud569\uc131 \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \uc18c\uac1c\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uac1c\uc694 \uba38\uc2e0\ub7ec\ub2dd\uc740 \uc54c\uace0\ub9ac\uc998\uacfc \ud1b5\uacc4 … \ub354 \ubcf4\uae30 “\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, GAN\uc73c\ub85c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131”<\/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-28664","post","type-post","status-publish","format-standard","hentry","category-29"],"yoast_head":"\n\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, GAN\uc73c\ub85c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131 - \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\/28664\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, GAN\uc73c\ub85c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ud000\ud2b8 \ud2b8\ub808\uc774\ub529\uc740 \ub370\uc774\ud130 \uae30\ubc18\uc73c\ub85c \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \uac70\ub798 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. \ub2e4\uc591\ud55c \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \ucc3e\uc544\ub0b4\uace0, \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc790\ub3d9 \ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uace0, Generative Adversarial Networks (GAN)\uc744 \ud1b5\ud574 \ud569\uc131 \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \uc18c\uac1c\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uac1c\uc694 \uba38\uc2e0\ub7ec\ub2dd\uc740 \uc54c\uace0\ub9ac\uc998\uacfc \ud1b5\uacc4 … \ub354 \ubcf4\uae30 "\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, GAN\uc73c\ub85c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/28664\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-10-27T16:14:25+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:59:34+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=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/atmokpo.com\/w\/28664\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/atmokpo.com\/w\/28664\/\"},\"author\":{\"name\":\"root\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\"},\"headline\":\"\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, GAN\uc73c\ub85c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131\",\"datePublished\":\"2024-10-27T16:14:25+00:00\",\"dateModified\":\"2024-11-26T06:59:34+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/atmokpo.com\/w\/28664\/\"},\"wordCount\":37,\"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\/28664\/\",\"url\":\"https:\/\/atmokpo.com\/w\/28664\/\",\"name\":\"\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, GAN\uc73c\ub85c \ud569\uc131 \ub370\uc774\ud130 \uc0dd\uc131 - 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