{"id":44637,"date":"2024-09-26T18:00:30","date_gmt":"2024-09-26T10:00:30","guid":{"rendered":"https:\/\/case.ntu.edu.tw\/blog\/?p=44637"},"modified":"2024-09-26T14:13:22","modified_gmt":"2024-09-26T06:13:22","slug":"%e6%a9%9f%e5%99%a8%e5%ad%b8%e7%bf%92%e5%9c%a8%e7%81%bd%e5%ae%b3%e8%a9%95%e4%bc%b0%e4%b8%ad%e7%9a%84%e6%87%89%e7%94%a8","status":"publish","type":"post","link":"https:\/\/case.ntu.edu.tw\/blog\/?p=44637","title":{"rendered":"\u6a5f\u5668\u5b78\u7fd2\u5728\u707d\u5bb3\u8a55\u4f30\u4e2d\u7684\u61c9\u7528"},"content":{"rendered":"

\u96a8\u8457\u6c23\u5019\u8b8a\u9077\u3001\u5404\u985e\u707d\u5bb3\u5982\uff1a\u6d2a\u6c34\u3001\u98b6\u98a8\u7b49\uff0c\u5c0d\u74b0\u5883\u3001\u4eba\u985e\u751f\u6d3b\u7522\u751f\u66f4\u5287\u70c8\u7684\u885d\u64ca\uff0cSDGs\u7684\u76f8\u95dc\u76ee\u6a19\u5982\uff1a\u76ee\u6a1911\u300c\u4fc3\u4f7f\u57ce\u5e02\u8207\u4eba\u985e\u5c45\u4f4f\u5177\u5305\u5bb9\u3001\u5b89\u5168\u3001\u97cc\u6027\u53ca\u6c38\u7e8c\u6027\u300d\u4e5f\u6210\u70ba\u5de8\u5927\u6311\u6230\uff0c\u5176\u4e2d\u768411.5\u5b50\u9805\u300c\u6e1b\u5c11\u81ea\u7136\u707d\u5bb3\u7684\u4e0d\u5229\u5f71\u97ff\u300d\u66f4\u662f\u5404\u754c\u707d\u5bb3\u6551\u63f4\u3001\u6e1b\u707d\u8a08\u756b\u7684\u91cd\u8981\u76ee\u6a19\u3002\u8fd1\u5e74\u4f86\uff0c\u806f\u5408\u570b\u4e16\u754c\u7ce7\u98df\u8a08\u5283\u7f72 (WFP) \u8207Google Research\u5408\u4f5c\uff0c\u5c07\u6a5f\u5668\u5b78\u7fd2\u5e36\u5165\u707d\u5bb3\u8a55\u4f30\u5834\u57df\uff0c\u4f60\u80fd\u60f3\u50cf\u6a5f\u5668\u5b78\u7fd2\u5982\u4f55\u5e6b\u52a9\u66f4\u591a\u53d7\u707d\u5c45\u6c11\u55ce\uff1f\u8b93\u6211\u5011\u4e00\u8d77\u4f86\u770b\u770b\u672c\u671f\u6587\u7ae0\uff01<\/strong><\/span><\/p>\n

\u64b0\u6587\uff5cFin<\/strong><\/p>\n

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\u57161\uff1a\u6d2a\u6c34\uff5c\u4f86\u6e90\uff1aWikimedia Commons<\/figcaption><\/figure>\n

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\u56e0\u6b64\uff0c\u707d\u5f8c\u5feb\u901f\u7372\u5f97\u5168\u9762\u3001\u6e96\u78ba\u7684\u8a55\u4f30\uff0c\u4fbf\u6210\u4e86\u6551\u63f4\u7d44\u7e54\u548c\u653f\u5e9c\u7684\u8feb\u5207\u9700\u6c42\u3002\u6709\u4e86\u9019\u4e9b\u8a55\u4f30\uff0c\u6551\u63f4\u7d44\u7e54\u624d\u80fd\u6e96\u78ba\u6551\u63f4\uff0c\u76f8\u95dc\u55ae\u4f4d\u624d\u80fd\u59a5\u5584\u5206\u914d\u8cc7\u6e90\u3002\u800c\u6a5f\u5668\u5b78\u7fd2\u7684\u52a0\u5165\uff0c\u8b93\u707d\u5bb3\u8a55\u4f30\u7684\u512a\u5316\u51fa\u73fe\u66d9\u5149\u3002<\/p>\n

\u00a0<\/strong>\u8209\u4f8b\u4f86\u8aaa\uff0c\u806f\u5408\u570b\u4e16\u754c\u7ce7\u98df\u8a08\u5283\u7f72 (WFP) \u8207Google Research\u5efa\u7acb\u4e86\u7531\u4eba\u5de5\u667a\u6167\u9a45\u52d5\u7684\u5c08\u6848\u2014\u2014\u300cSKAI\u300d\uff0c\u5b83\u7d50\u5408\u4e86\u7d71\u8a08\u65b9\u6cd5\u3001\u6578\u64da\u548c\u73fe\u4ee3\u904b\u7b97\u6280\u8853\uff0c\u81ea\u52d5\u5730\u57f7\u884c\u7279\u5b9a\u4efb\u52d9\u3002\u5b83\u61c9\u7528\u4e86\u96fb\u8166\u8996\u89ba\u4f86\u8a55\u4f30\u5efa\u7bc9\u7269\u7684\u640d\u58de\u60c5\u5f62\uff0c\u800c\u96fb\u8166\u6f14\u7b97\u6cd5\u53ef\u4ee5\u89e3\u91cb\u5f9e\u8996\u89ba\u7d20\u6750\u4e2d\u63d0\u53d6\u7684\u8cc7\u8a0a\uff0c\u4f8b\u5982\uff1a\u53d7\u885d\u7a81\u3001\u6c23\u5019\u4e8b\u4ef6\u6216\u5176\u4ed6\u707d\u5bb3\u885d\u64ca\u5730\u5340\u7684\u885b\u661f\u5716\u50cf\uff0c\u800c\u6b64\u8a55\u4f30\u6d41\u7a0b\u7684\u6838\u5fc3\u662f\u5c08\u70baSKAI\u958b\u767c\u7684\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u3002<\/p>\n

 <\/p>\n

\u4ec0\u9ebc\u662f\u6a5f\u5668\u5b78\u7fd2\uff1f<\/strong><\/span><\/h6>\n

\u6a5f\u5668\u5b78\u7fd2 (Machine Learning) \u88ab\u8996\u70ba\u4eba\u5de5\u667a\u6167\u7684\u4e00\u500b\u5b50\u96c6\u3002\u6839\u64da\u5b78\u8005Jordan\u548cMitchell (2015) \u7684\u8aaa\u6cd5\uff1a\u300c\u6a5f\u5668\u5b78\u7fd2\u9019\u500b\u9818\u57df\u6240\u95dc\u6ce8\u7684\u554f\u984c\u662f\uff0c\u5982\u4f55\u767c\u5c55\u8a08\u7b97\u6a5f\uff0c\u8b93\u5b83\u80fd\u900f\u904e\u7d93\u9a57\u4f86\u81ea\u52d5\u6539\u5584\uff1f\u300d\u4ed6\u5011\u63a5\u8457\u8aaa\u660e\uff1a\u300c\u4e00\u500b\u5b78\u7fd2\u554f\u984c\u53ef\u4ee5\u5b9a\u7fa9\u70ba\u900f\u904e\u67d0\u7a2e\u985e\u578b\u7684\u8a13\u7df4\u7d93\u9a57\uff0c\u5728\u57f7\u884c\u67d0\u4e9b\u4efb\u52d9\u6642\uff0c\u63d0\u9ad8\u67d0\u4e9b\u6548\u80fd\u6307\u6a19\u7684\u554f\u984c\u3002\u4f8b\u5982\uff0c\u5728\u5b78\u7fd2\u5075\u6e2c\u4fe1\u7528\u5361\u8a50\u6b3a\u6642\uff0c\u4efb\u52d9\u662f\u70ba\u4efb\u4f55\u7d66\u5b9a\u7684\u4fe1\u7528\u5361\u4ea4\uf9e0\u5206\u914d\u300e\u8a50\u6b3a\u300f\u6216\u300e\u975e\u8a50\u6b3a\u300f\u6a19\u7c64\u3002\u8981\u6539\u9032\u7684\u6548\u80fd\u6307\u6a19\u53ef\u80fd\u662f\u6b64\u8a50\u6b3a\u5206\u985e\u5668\u7684\u6e96\u78ba\u6027\uff0c\u8a13\u7df4\u9ad4\u9a57\u53ef\u80fd\u5305\u62ec\u6b77\u53f2\u4fe1\u7528\u5361\u4ea4\uf9e0\u7684\u96c6\u5408\uff0c\u6bcf\u7b46\u4ea4\uf9e0\u5728\u56de\u9867\u6642\u90fd\u88ab\u6a19\u8a18\u70ba\u8a50\u6b3a\u6216\u975e\u8a50\u6b3a\u3002\u300d<\/p>\n

\u548c\u524d\u4f8b\u6709\u7570\u66f2\u540c\u5de5\u4e4b\u5999\u7684SAKI\u5c08\u6848\u4e2d\uff0c\u5718\u968a\u5e0c\u671b\u6a21\u578b\u80fd\u6539\u9032\u5206\u8fa8\u53d7\u640d\u5efa\u7bc9\u7269\u7684\u300c\u6e96\u78ba\u5ea6\u300d\uff0c\u800c\u6a21\u578b\u7684\u8a13\u7df4\u8cc7\u6599\u4f7f\u7528\u4e86\u6709\u5c08\u5bb6\u6a19\u8a18\u7684\u904e\u53bb\u707d\u5bb3\u5716\u50cf\u3002\u7d93\u904e\u8a13\u7df4\u7684\u6a21\u578b\uff0c\u53ef\u5206\u8fa8\u300c\u53d7\u640d\u300d\u548c\u300c\u672a\u53d7\u640d\u300d\u5efa\u7bc9\u7269\u7684\u5716\u50cf\uff0c\u5728\u5e7e\u5206\u9418\u5167\u5206\u6790\u6574\u5ea7\u57ce\u5e02\uff0c\u6709\u5229\u4eba\u54e1\u8fc5\u901f\u6551\u63f4\u3001\u5206\u914d\u8cc7\u6e90\u3002<\/p>\n

\"\"
\u57162\uff1a\u8a13\u7df4\u8cc7\u6599\uff1a\u6bcf\u7d44\u5716\u7684\u5de6\u5716\u70ba\u707d\u524d\u3001\u53f3\u5716\u70ba\u707d\u5f8c\uff0ca\u3001b\u3001c\u5206\u5225\u662f\u6d77\u5730\u3001\u58a8\u897f\u54e5\u3001\u5370\u5c3c\u5730\u9707 \uff5c\u4f86\u6e90\uff1a\u53c3\u8003\u6587\u737b4<\/figcaption><\/figure>\n

\u6b64\u6a21\u578b\u9084\u6709\u4e00\u9805\u7279\u9ede\uff0c\u662f\u904b\u7528\u4e86\u300c\u5377\u7a4d\u795e\u7d93\u7db2\u8def\u300d\uff08Convolutional Neural Networks, CNN\uff09\u3002\u6839\u64daKattenborn\u7b49\u5b78\u8005 (2021) \u6240\u8aaa\uff1a\u300cCNN\u88ab\u8a2d\u8a08\u65bc\u5b78\u7fd2\u7a7a\u9593\u7279\u5fb5\uff0c\u4f8b\u5982\uff1a\u908a\u7de3\u3001\u89d2\u3001\u7d0b\u7406\u6216\u66f4\u62bd\u8c61\u7684\u5f62\u72c0\uff0c\u6700\u80fd\u63cf\u8ff0\u51fa\u76ee\u6a19\u7684\u985e\u5225\u6216\u6578\u91cf\u3002\u300d<\/p>\n

 <\/p>\n

SAKI\u5c08\u6848\u4e2d\uff0c\u6a21\u578b\u7684\u8a13\u7df4\u904e\u7a0b\uff1f<\/strong><\/span><\/h6>\n

2019\u5e74\uff0c\u7814\u7a76\u5718\u968a\u70ba\u6b64\u5c08\u6848\u5efa\u7acb\u4e86\u6db5\u84cb\u4e09\u7a2e\u5730\u5340\u5730\u9707\u7684\u8cc7\u6599\u96c6\u63d0\u4f9b\u8a13\u7df4\u2014\u20142010\uf98e\u6d77\u5730\u5730\u9707\u30012017\uf98e\u58a8\u897f\u54e5\u57ce\u5730\u9707\u548c2018\uf98e\u5370\u5c3c\u5730\u9707\u3002\u4e0d\u904e\uff0c\u7531\u65bc\u5be6\u969b\u707d\u5bb3\u7684\u7a2e\u985e\u591a\u5143\uff0c\u904e\u53bb\u63d0\u4f9b\u6a21\u578b\u7684\u707d\u96e3\u8a13\u7df4\u6578\u64da\u985e\u578b\u6709\u9650\uff0c\u80fd\u5426\u9806\u5229\u8a55\u4f30\u65b0\u5730\u9ede\u7684\u707d\u96e3\u4ecd\u662f\u6311\u6230\uff0c\u7814\u7a76\u5718\u968a\u7406\u60f3\u7684\u6a21\u578b\u662f\u80fd\u5920\u6e96\u78ba\u8a55\u4f30\u5168\u7403\u4efb\u4f55\u5730\u65b9\u7684\u707d\u96e3\u9020\u6210\u7684\u5efa\u7bc9\u7269\u640d\u58de\u3002<\/p>\n

\u56e0\u6b64\uff0c\u8fd1\u5e74\u4f86\uff0c\u4ed6\u5011\u9678\u7e8c\u65b0\u589e\u8a13\u7df4\u8cc7\u6599\uff0c\u5305\u62ec2020\u5e74\u9ece\u5df4\u5ae9\u8c9d\u9b6f\u7279\u6e2f\u7206\u70b8\u4e8b\u4ef6\u548c2021\u5e74\u7684\u6590\u6fdf\u98b6\u98a8\u96c5\u85a9 (Yasa)\u30022020\u5e74\u8c9d\u9b6f\u7279\u6e2f\u7206\u70b8\u4e8b\u4ef6\u7684\u8cc7\u6599\u63ed\u793a\u4e86\u885b\u661f\u5f71\u50cf\u7684\u91cd\u8981\u77e5\u8b58\u2014\u2014\u885b\u661f\u5f71\u50cf\u96e3\u4ee5\u6aa2\u6e2c\u5230\u7531\u65bc\u7206\u70b8\u6027\u8cea\u548c\u5074\u5411\u529b\u5c0e\u81f4\u7684\u5efa\u7bc9\u7269\u5782\u76f4\u8868\u9762\u640d\u58de\uff0c\u5982\uff1a\u7a97\u6236\u7834\u788e\u548c\u7246\u58c1\u7834\u88c2\uff0c\u56e0\u70ba\u885b\u661f\u5f71\u50cf\u662f\u5f9e\u4e0a\u65b9\u62cd\u651d\u7684\u3002<\/p>\n

\u8b80\u5230\u9019\u88e1\uff0c\u4f60\u53ef\u80fd\u6703\u597d\u5947\uff1aSAKI\u7684\u6a21\u578b\u548c\u50b3\u7d71\u7684\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u76f8\u6bd4\uff0c\u6709\u4f55\u4e0d\u540c\u5462\uff1f\u50b3\u7d71\u7684\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u5fc5\u9808\u4f7f\u7528\u7531\u4eba\u985e\u5c08\u5bb6\u624b\u52d5\u6a19\u8a18\u7684\u6578\u5343\u500b\u7bc4\u4f8b\u5f71\u50cf\u4f86\u8a13\u7df4\uff0c\u5341\u5206\u8017\u6642\uff0c\u800c\u57282021\u5e74\uff0c\u4f7f\u7528\u00a0\u00a0\u534a\u76e3\u7763\u5b78\u7fd2 (Semi-Supervised Learning, SSL) \u65b9\u6cd5\u8a13\u7df4\u7684\u6a21\u578b\uff0c\u53ea\u9700\u6578\u767e\u500b\u6a19\u8a18\u7bc4\u4f8b\u5c31\u80fd\u5be6\u73fe\u9ad8\u6e96\u78ba\u5ea6\uff0c\u63d0\u5347\u7372\u5f97\u6e96\u78ba\u7d50\u679c\u7684\u901f\u5ea6\uff0c\u547c\u61c9\u4e86\u707d\u5f8c\u9700\u8981\u5feb\u901f\u8a55\u4f30\u7684\u60c5\u5883\u3002<\/p>\n

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\u57163\uff1a 2010\u5e74\u6d77\u5730\u5730\u9707\u524d\u592a\u5b50\u6e2f\u7684\u885b\u661f\u7167\u7247(\u975eSAKI\u5c08\u6848\u63d0\u4f9b)\uff5c\u4f86\u6e90\uff1aWikimedia Commons<\/figcaption><\/figure>\n

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\u6b64\u6a21\u578b\u7684\u5be6\u6e2c\u6210\u679c\uff1f<\/strong><\/span><\/h6>\n

2023\u5e74\uff0c\u5728\u571f\u8033\u5176\u548c\u6558\u5229\u4e9e\u5927\u5730\u9707\u5f8c\uff0c\u6b64\u6a21\u578b\u5c55\u793a\u4e86\u591a\u6a23\u529f\u80fd\uff1a<\/p>\n

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  1. \u7cbe\u6e96\u8a55\u4f30\uff1a\u6a21\u578b\u8a55\u4f30\u4e86\u7d0460\u842c\u68df\u5efa\u7bc9\u7269\uff0c\u6e96\u78ba\u7387\u8d85\u904e81%\u3002<\/li>\n
  2. \u5feb\u901f\u6db5\u84cb\u5927\u7bc4\u570d\u5340\u57df\uff1a\u5728\u4e0d\u5230\u4e00\u9031\u5167\uff0c\u8a55\u4f30\u7bc4\u570d\u64f4\u53ca530\u5e73\u65b9\u516c\u91cc\u5340\u57df\u3002<\/li>\n
  3. \u63d0\u4f9b\u6709\u50f9\u503c\u6578\u64da\uff1a\u6a21\u578b\u8490\u96c6\u66f4\u591a\u885b\u661f\u5716\u50cf\u548c\u5efa\u7269\u53d7\u640d\u6578\u64da\uff0c\u70ba\u6c7a\u7b56\u8005\u63d0\u4f9b\u5fc5\u8981\u8cc7\u8a0a\u4f86\u898f\u5283\u3001\u57f7\u884c\u6551\u63f4\u3002<\/li>\n<\/ol>\n

    \u6b64\u6a21\u578b\u5728\u4e0d\u540c\u985e\u578b\u7684\u707d\u5bb3\u2014\u2014<\/strong>2022\u5e74\u5df4\u57fa\u65af\u5766\u6d2a\u707d\u4e5f\u767c\u63ee\u4f5c\u7528\uff0c\u5206\u6790\u53d7\u6d2a\u6c34\u5f71\u97ff\u7684\u5730\u5340\uff0c\u652f\u63f4\u7576\u5c40\u6551\u707d\u8a55\u4f30\uff0c\u8a55\u4f30\u7bc4\u570d\u70ba8,000\u5e73\u65b9\u516c\u91cc\uff0c\u5e6b\u52a9\u4e86250\u842c\u4eba\u3002<\/p>\n

     <\/p>\n

    \u6a5f\u5668\u5b78\u7fd2\u61c9\u7528\u5728\u707d\u5bb3\u8a55\u4f30\u9818\u57df\u7684\u6311\u6230<\/strong><\/span><\/h6>\n

    \u5f9e\u524d\u4f8b\u53ef\u77e5\uff0c\u6a5f\u5668\u5b78\u7fd2\u5728\u707d\u5f8c\u8a55\u4f30\u548c\u6551\u63f4\u884c\u52d5\u4e2d\u6709\u5de8\u5927\u6f5b\u529b\u63d0\u5347\u6548\u7387\uff0c\u4f46\u4ecd\u9762\u81e8\u6311\u6230\uff0c\u5305\u62ec\u9700\u8981\u5927\u91cf\u9ad8\u89e3\u6790\u5ea6\u7684\u885b\u661f\u5716\u50cf\u63d0\u4f9b\u8a13\u7df4\uff0c\u56e0\u6b64\uff0cWFP\u5e0c\u671b\u66f4\u591a\u79c1\u4eba\u548c\u6a5f\u69cb\u958b\u653e\u76f8\u95dc\u5716\u50cf\u7528\u65bc\u4eba\u9053\u4e3b\u7fa9\u7528\u9014\u3002\u6b64\u5916\uff0c\u9700\u8b93\u5404\u5730\u5c45\u6c11\u3001\u653f\u5e9c\u7b49\u76f8\u95dc\u4eba\u58eb\u4e86\u89e3\u6a5f\u5668\u5b78\u7fd2\u7684\u6f5b\u529b\uff0c\u89e3\u9664\u4ed6\u5011\u5c0d\u6280\u8853\u7684\u7591\u616e\uff0c\u4ee5\u4fbf\u5728\u707d\u5bb3\u767c\u751f\u6642\u80fd\u5be6\u969b\u904b\u7528\u5b83\u7684\u6280\u8853\u3001\u5171\u540c\u61c9\u8b8a\uff0c\u6e1b\u5c11\u707d\u5bb3\u5f71\u97ff\u3002<\/p>\n

     <\/p>\n

    \n

    \u53c3\u8003\u6587\u737b<\/strong><\/p>\n

      \n
    1. Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260.<\/a><\/li>\n
    2. The SKAI isn\u2019t the limit: How WFP uses satellite imagery and machine learning in emergencies. (2024).WFP<\/a><\/li>\n
    3. Lee, J., Xu, J. Z., Sohn, K., Lu, W., Berthelot, D., Gur, I., ... & Kowatsch, B. (2020). Assessing post-disaster damage from satellite imagery using semi-supervised learning techniques. arXiv preprint arXiv:2011.14004.<\/a><\/li>\n
    4. Xu, J. Z., Lu, W., Li, Z., Khaitan, P., & Zaytseva, V. (2019). Building damage detection in satellite imagery using convolutional neural networks. arXiv preprint arXiv:1910.06444.<\/a><\/li>\n
    5. Machine Learning-based Damage Assessment for Disaster Relief. (2024). Joseph Xu, Senior Software Engineer and Pranav Khaitan, Engineering Lead, Google Research<\/a><\/li>\n
    6. SKAI. (2024).WFP<\/a><\/li>\n
    7. The benefits of machine learning in emergencies from river DEEP to mountain SKAI. (2024).WFP<\/a><\/li>\n
    8. How Do AI and Machine Learning Differ? (2024). California Institute of Technology<\/a><\/li>\n
    9. Revolutionizing Disaster Response with SKAI. (2024).WFP<\/a><\/li>\n
    10. Sers, G\u00fcnter. (2024). Bundesarchiv B 422 Bild-0086, K\u00f6ln, Rheinufer, Hochwasser. Wikimedia Commons (No changes were made)<\/a><\/li>\n
    11. DLR. (2024). Haiti satellite image before earthquake on 12 January 2010 Wikimedia Commons (No changes were made)<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

      \u96a8\u8457\u6c23\u5019\u8b8a\u9077\u3001\u5404\u985e\u707d\u5bb3\u5982\uff1a\u6d2a\u6c34\u3001\u98b6\u98a8\u7b49\uff0c\u5c0d\u74b0\u5883\u3001\u4eba\u985e\u751f\u6d3b\u7522\u751f\u66f4\u5287\u70c8\u7684\u885d\u64ca\uff0cSDGs\u7684\u76f8\u95dc\u76ee\u6a19\u5982\uff1a\u76ee\u6a1911\u300c\u4fc3\u4f7f\u57ce\u5e02\u8207\u4eba\u985e\u5c45\u4f4f\u5177\u5305\u5bb9\u3001\u5b89\u5168\u3001\u97cc\u6027\u53ca\u6c38\u7e8c\u6027\u300d\u4e5f\u6210\u70ba\u5de8\u5927\u6311\u6230\uff0c\u5176\u4e2d\u768411.5\u5b50\u9805\u300c\u6e1b\u5c11\u81ea\u7136\u707d\u5bb3\u7684\u4e0d\u5229\u5f71\u97ff\u300d\u66f4\u662f\u5404\u754c\u707d\u5bb3\u6551\u63f4\u3001\u6e1b\u707d\u8a08\u756b\u7684\u91cd\u8981\u76ee\u6a19\u3002\u8fd1\u5e74\u4f86\uff0c\u806f\u5408\u570b\u4e16\u754c\u7ce7\u98df\u8a08\u5283\u7f72 (WFP) \u8207Google Research\u5408\u4f5c\uff0c\u5c07\u6a5f\u5668\u5b78\u7fd2\u5e36\u5165\u707d\u5bb3\u8a55\u4f30\u5834\u57df\uff0c\u4f60\u80fd\u60f3\u50cf\u6a5f\u5668\u5b78\u7fd2\u5982\u4f55\u5e6b\u52a9\u66f4\u591a\u53d7\u707d\u5c45\u6c11\u55ce\uff1f\u8b93\u6211\u5011\u4e00\u8d77\u4f86\u770b\u770b\u672c\u671f\u6587\u7ae0\uff01<\/p>\n","protected":false},"author":20,"featured_media":44640,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17,3293,4988,7189],"tags":[6680,3006,792,1712,7215],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/case.ntu.edu.tw\/blog\/wp-content\/uploads\/2024\/09\/\u5716-1\uff1a\u6d2a\u6c34\uff5c\u4f86\u6e90\uff1aWikimedia-Commons.jpg","_links":{"self":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts\/44637"}],"collection":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=44637"}],"version-history":[{"count":1,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts\/44637\/revisions"}],"predecessor-version":[{"id":44641,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts\/44637\/revisions\/44641"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/media\/44640"}],"wp:attachment":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=44637"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=44637"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=44637"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}