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\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:\u4f55\u607a\u660e\u7684ResNet\uff0c\u6210\u4e3a21\u4e16\u7eaa\u88ab\u5f15\u91cf\u6700\u591a\u8bba\u6587\uff0cNature\u6700\u65b0\u7edf\u8ba1<\/a><\/p>\n

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\u300a\u81ea\u7136\u300b\u6742\u5fd7\u7edf\u8ba1\u4e86 5 \u4e2a\u6570\u636e\u5e93\uff0c\u7ed9\u51fa\u4e86\u8bba\u6587\u5f15\u7528 Top 25 \u540d\u5355\u3002<\/p>\n<\/blockquote>\n

21 \u4e16\u7eaa\u88ab\u5f15\u7528\u6700\u591a\u7684\u8bba\u6587\u6709\u54ea\u4e9b\uff1f<\/p>\n

\u5927\u5bb6\u4e0d\u7528\u53bb\u7edf\u8ba1\u4e86\uff0c\u300a\u81ea\u7136\u300b\u7ed9\u51fa\u4e86\u4e00\u4e2a\u6700\u65b0 Top 25 \u6392\u540d\u3002<\/p>\n

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\u5b8c\u6574\u6392\u540d\u5730\u5740\uff1ahttps:\/\/www.nature.com\/magazine-assets\/d41586-025-01125-9\/50860378<\/p>\n

\u6392\u540d\u7b2c\u4e00\u7684\u662f\u5fae\u8f6f\u5728 2016 \u5e74\u53d1\u5e03\u7684 ResNets \u7814\u7a76<\/strong>\uff0c\u8fd9\u662f\u4e00\u7bc7\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u7684\u7ecf\u5178\u8bba\u6587\u3002<\/p>\n

ResNets \u4f5c\u4e3a\u4e00\u79cd\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff0c\u662f\u6df1\u5ea6\u5b66\u4e60\u4ee5\u53ca\u540e\u7eed AI \u8fdb\u6b65\u7684\u57fa\u7840\u3002\u8fd9\u9879\u5de5\u4f5c\u6700\u521d\u4e8e 2015 \u5e74\u5e95\u4ee5\u9884\u5370\u672c\u5f62\u5f0f\u53d1\u5e03\uff0c\u4f5c\u8005\u5305\u62ec\u4f55\u607a\u660e\u3001\u5f20\u7965\u96e8\u3001\u4efb\u5c11\u537f\u548c\u5b59\u5251\u3002ResNets \u539f\u59cb\u8bba\u6587\u5728 2016 \u5c31\u83b7\u5f97\u4e86 CVPR \u6700\u4f73\u8bba\u6587\u5956\u3002<\/span><\/p>\n

<\/a><\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/pdf\/1512.03385<\/p>\n

\u540e\u6765 AI \u9886\u57df\u91cd\u5927\u8fdb\u5c55\uff0c\u90fd\u6df1\u53d7 ResNets \u7684\u5f71\u54cd\uff0c\u5305\u62ec\u56f4\u68cb AI\uff08AlphaGo\uff09\u3001\u86cb\u767d\u8d28\u7ed3\u6784\u9884\u6d4b\uff08AlphaFold\uff09\u5230\u540e\u6765\u7684\u8bed\u8a00\u6a21\u578b\uff08ChatGPT\uff09\u7b49\u3002<\/p>\n

\u6b64\u5916\uff0c\u300c\u968f\u673a\u68ee\u6797\uff08Random forests (2001)\uff09\u300d\uff0c\u300cAttention is all you need (2017)\u300d\u3001\u300cImageNet classification with deep convolutional neural networks (2017)\u300d\u4e5f\u4f4d\u5c45 top 10 \u699c\u5355\u3002<\/p>\n

\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u4ee5\u4e0a\u7ed3\u8bba\u662f\u300a\u81ea\u7136\u300b\u56e2\u961f\u9009\u53d6\u4e86 5 \u4e2a\u6570\u636e\u5e93<\/strong>\uff08Web of Science\u3001Scopus\u3001OpenAlex\u3001Dimensions\u3001Google Scholar\uff09\u7684\u7edf\u8ba1\u7ed3\u679c\uff0c\u8fd9\u4e9b\u6570\u636e\u5e93\u6db5\u76d6\u4e86 21 \u4e16\u7eaa\u53d1\u8868\u7684\u6570\u5343\u4e07\u7bc7\u8bba\u6587<\/strong>\uff1aResNets \u5728\u5176\u4e2d\u4e24\u4e2a\u6570\u636e\u5e93\u4e2d\u5f15\u7528\u91cf\u6700\u9ad8\uff0c\u5728\u53e6\u5916\u4e24\u4e2a\u4e2d\u6392\u540d\u7b2c\u4e8c\uff0c\u6700\u540e\u4e00\u4e2a\u4f4d\u5217\u7b2c\u4e09 \u2014\u2014 \u7efc\u5408\u6765\u770b\uff0c\u5176\u5f15\u7528\u6b21\u6570\u7684\u4e2d\u4f4d\u6570\u6392\u540d\u5728\u4e94\u4e2a\u6570\u636e\u5e93\u4e2d\u4f4d\u5c45\u699c\u9996\u3002<\/p>\n

\u5982\u679c\u4ece\u5355\u4e00\u6307\u6807\u6765\u770b\uff0cResNets \u5e76\u975e\u5728\u6240\u6709\u6570\u636e\u5e93\u4e2d\u90fd\u662f\u5f15\u7528\u91cf\u6700\u9ad8\u7684\u3002\u6839\u636e\u8c37\u6b4c\u5b66\u672f\uff08Google Scholar\uff09\u7684\u6570\u636e\uff08\u5176\u56e2\u961f\u5411\u300a\u81ea\u7136\u300b\u63d0\u4f9b\u4e86\u9ad8\u5f15\u8bba\u6587\u699c\u5355\uff09\uff0c\u8be5\u8bba\u6587\u4ee5 25.4 \u4e07\u6b21\u5f15\u7528\u4f4d\u5c45\u7b2c\u4e8c\u3002\u800c\u5728\u7f8e\u56fd\u79d1\u777f\u552f\u5b89\u516c\u53f8\u65d7\u4e0b\u7684 Web of Science \u6570\u636e\u5e93\u4e2d\uff08\u8be5\u5e93\u6536\u5f55\u7684\u671f\u520a\u8303\u56f4\u8f83\u7a84\uff09\uff0c\u5b83\u4ec5\u4ee5 10 \u4e07\u4f59\u6b21\u5f15\u7528\u6392\u540d\u7b2c\u4e09\u3002\u56e0\u800c\uff0c\u5927\u5bb6\u9700\u8981\u76f8\u5bf9\u6765\u770b\u5f85\u8fd9\u6b21\u6392\u540d\u3002<\/p>\n

\u4e0d\u8fc7\uff0c21 \u4e16\u7eaa\u7684\u91cd\u5927\u7a81\u7834\u4e0d\u53ea\u662f AI \u9886\u57df\uff0c\u5e0c\u683c\u65af\u73bb\u8272\u5b50\u7684\u53d1\u73b0\u3001\u5f15\u529b\u6ce2\u7684\u9996\u6b21\u6d4b\u91cf\u7b49\u90fd\u79f0\u5f97\u4e0a\u5de8\u5927\u7684\u8fdb\u6b65\uff0c\u7136\u800c\uff0c\u8fd9\u4e9b\u7a81\u7834\u6027\u6210\u679c\u5728 2000 \u5e74\u4ee5\u6765\u88ab\u5f15\u7528\u91cf\u6700\u9ad8\u7684\u8bba\u6587\u4e2d\u5374\u65e0\u4e00\u4e0a\u699c\u3002<\/p>\n

\u539f\u56e0\u4e3a\u4f55\uff1f<\/p>\n

\u63a5\u4e0b\u6765\uff0cNature \u8fd9\u7bc7\u6587\u7ae0\u4ecb\u7ecd\u4e86\u5176\u4ed6top 25\u8bba\u6587\u4ee5\u53ca\u5b83\u4eec\u6210\u4e3a\u300c\u5f15\u7528\u5de8\u5934\u300d\u7684\u539f\u56e0\u3002<\/p>\n

AI \u6210\u4e3a\u4e8c\u5341\u4e00\u4e16\u7eaa\u88ab\u5f15\u7528\u6b21\u6570\u6700\u591a\u7684\u8bba\u6587<\/strong><\/p>\n

AI \u6559\u7236 Geoffrey Hinton \u6307\u51fa\uff0cAI \u8bba\u6587\u5728\u5f15\u7528\u65b9\u9762\u5177\u6709\u5929\u7136\u4f18\u52bf\uff0cAI \u9886\u57df\u4e0e\u4f17\u591a\u9886\u57df\u76f8\u5173\u8054<\/strong>\uff0c21 \u4e16\u7eaa\u4ee5\u6765\u89c1\u8bc1\u4e86\u5feb\u901f\u7684\u6280\u672f\u8fdb\u6b65\u548c\u5927\u91cf\u5b66\u672f\u8bba\u6587\u7684\u6d8c\u73b0\u3002<\/p>\n

Hinton \u56e0\u5728 AI \u9886\u57df\u7684\u8d21\u732e\uff0c\u53bb\u5e74\u83b7\u5f97\u4e86\u8bfa\u8d1d\u5c14\u7269\u7406\u5b66\u5956\u3002<\/p>\n

\u8bb8\u591a\u4eba\u8ba4\u4e3a\uff0c\u6df1\u5ea6\u5b66\u4e60\u7684\u9769\u547d\u6027\u53d1\u5c55\uff0c\u7279\u522b\u662f\u591a\u5c42\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u5e7f\u6cdb\u5b9e\u7528\u6027\uff0c\u5f97\u76ca\u4e8e Hinton \u5728 2012 \u5e74\u5171\u540c\u64b0\u5199\u7684\u8bba\u6587\u300aImageNet classification with deep convolutional neural networks\u300b\u3002\u8fd9\u7bc7\u8bba\u6587\u4ecb\u7ecd\u4e86\u540e\u6765\u88ab\u547d\u540d\u4e3a AlexNet \u7684\u7f51\u7edc\uff0c\u5176\u5728\u56fe\u50cf\u8bc6\u522b\u548c\u6807\u8bb0\u7ade\u8d5b\u4e2d\u8868\u73b0\u4f18\u4e8e\u5176\u4ed6\u65b9\u6cd5\uff0c\u6210\u4e3a 21 \u4e16\u7eaa\u5f15\u7528\u6b21\u6570\u7b2c 8 \u9ad8\u7684\u8bba\u6587\u3002<\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3065386<\/p>\n

\u6b64\u5916\uff0cHinton \u53ca\u5176\u5408\u8457\u8005\u64b0\u5199\u7684\u5173\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u7efc\u8ff0\u8bba\u6587\u6392\u540d\u7b2c 16\u3002<\/p>\n

\u800c 2009 \u5e74\u674e\u98de\u98de\u7684\u8bba\u6587\u300aImageNet: A Large-Scale Hierarchical Image Database\u300b\u4f5c\u4e3a\u8bad\u7ec3\u6570\u636e\u96c6\u6839\u57fa\uff0c\u6392\u540d\u7b2c 24\u3002<\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/ieeexplore.ieee.org\/document\/5206848<\/p>\n

\u4e09\u5e74\u540e\uff0c\u4e00\u7bc7\u5bf9 AlexNet \u67b6\u6784\u8fdb\u884c\u4fee\u6539\u7684\u8bba\u6587\u63cf\u7ed8\u4e86\u4e00\u79cd\u79f0\u4e3a U-net \u7684\u65b0\u7f51\u7edc\uff0c\u5176\u5728\u56fe\u50cf\u5904\u7406\u4e0a\u66f4\u9ad8\u6548\uff0c\u73b0\u6392\u540d\u7b2c 12\uff0c\u5f53\u65f6\u8be5\u8bba\u6587\u5dee\u70b9\u56e0\u7f3a\u4e4f\u65b0\u610f\u800c\u88ab\u4f1a\u8bae\u62d2\u7edd\u3002\u5171\u540c\u4f5c\u8005 Olaf Ronneberger \u56e0\u8fd9\u4e00\u5de5\u4f5c\u800c\u52a0\u5165 DeepMind\uff0c\u4ed6\u8868\u793a\uff0cU-net \u4ecd\u7136\u662f\u8bb8\u591a\u6269\u6563\u6a21\u578b\u4e2d\u56fe\u50cf\u751f\u6210\u7684\u4e3b\u8981\u57fa\u7840\u3002<\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1505.04597<\/p>\n

2017 \u5e74\uff0c\u8c37\u6b4c\u7814\u7a76\u56e2\u961f\u63a8\u51fa\u9898\u4e3a\u300aAttention is all you need\u300b\u7684\u8bba\u6587\uff0c\u4ecb\u7ecd\u4e86 Transformer \u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u3002Transformer \u901a\u8fc7\u9ad8\u6548\u5b9e\u73b0\u81ea\u6ce8\u610f\u529b\u673a\u5236\uff0c\u4f7f\u7f51\u7edc\u5b66\u4e60\u65f6\u80fd\u4f18\u5148\u5904\u7406\u76f8\u5173\u4fe1\u606f\uff0c\u5e76\u6210\u4e3a\u63a8\u52a8\u7c7b\u4f3c ChatGPT \u7684\u5927\u578b\u8bed\u8a00\u6a21\u578b\u53d1\u5c55\u7684\u5173\u952e\u3002\u8be5\u8bba\u6587\u662f\u672c\u4e16\u7eaa\u5f15\u7528\u6b21\u6570\u7b2c 7 \u9ad8\u7684\u3002<\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/pdf\/1706.03762<\/p>\n

\u5f00\u6e90\u6280\u672f\u5728\u673a\u5668\u5b66\u4e60\u7684\u65e9\u671f\u63a8\u52a8\u4e86\u5176\u5f15\u7528\u7387\u7684\u63d0\u5347\u3002\u300aRandom forests\u300b\u662f\u7b2c 6 \u9ad8\u5f15\u7528\u7684\u8bba\u6587\uff0c\u4ecb\u7ecd\u4e86\u4e00\u79cd\u4f18\u5316\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u3002\u72b9\u4ed6\u5dde\u7acb\u5927\u5b66\u7edf\u8ba1\u5b66\u5bb6 Adele Cutler \u4e0e\u5df2\u6545\u7f8e\u56fd\u7edf\u8ba1\u5b66\u5bb6 Leo Breiman \u5171\u540c\u6269\u5c55\u4e86\u8fd9\u4e00\u65b9\u6cd5\u3002Cutler \u8868\u793a\uff0c\u8be5\u8bba\u6587\u53d7\u6b22\u8fce\u7684\u539f\u56e0\u5728\u4e8e\u5176\u5f00\u6e90\u3001\u514d\u8d39\u5e76\u6613\u4e8e\u4f7f\u7528\uff0c\u4e14\u529f\u80fd\u5353\u8d8a\uff0c\u65e0\u9700\u5927\u91cf\u5b9a\u5236\u5373\u53ef\u6267\u884c\u3002<\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/link.springer.com\/article\/10.1023\/A:1010933404324<\/p>\n

\u8bb8\u591a AI \u8bba\u6587\u5e38\u5728\u540c\u884c\u8bc4\u5ba1\u524d\u4ee5\u9884\u5370\u672c\u5f62\u5f0f\u53d1\u5e03\uff0c\u5bfc\u81f4\u5f15\u7528\u7edf\u8ba1\u590d\u6742\u5316<\/strong>\u3002\u5546\u4e1a\u6570\u636e\u5e93\u901a\u5e38\u4e0d\u8ddf\u8e2a\u9884\u5370\u672c\u5f15\u7528\uff0c\u6216\u672a\u80fd\u5c06\u5176\u4e0e\u6b63\u5f0f\u53d1\u8868\u6587\u7ae0\u7684\u5f15\u7528\u5408\u5e76\uff0c\u81f4\u4f7f\u5b9e\u9645\u5f15\u7528\u91cf\u88ab\u4f4e\u4f30\u3002\u8377\u5170\u83b1\u987f\u5927\u5b66\u9000\u4f11\u79d1\u5b66\u8ba1\u91cf\u5b66\u4e13\u5bb6 Paul Wouters \u6307\u51fa\uff0c\u968f\u7740\u9884\u5370\u672c\u5f15\u7528\u65e5\u76ca\u666e\u53ca\uff0c\u6570\u636e\u5e93\u4e9f\u9700\u5f00\u53d1\u65b0\u65b9\u6cd5\u6574\u5408\u8fd9\u7c7b\u5f15\u7528\u6570\u636e\u3002<\/p>\n

\u636e\u975e\u8425\u5229\u5b66\u672f\u670d\u52a1\u516c\u53f8 OurResearch \u7684 Jason Priem \u6240\u8ff0\uff0cOpenAlex \u6570\u636e\u5e93\uff08\u300a\u81ea\u7136\u300b\u6587\u7ae0\u7684\u4e00\u4e2a\u6765\u6e90\uff09\u5c1d\u8bd5\u901a\u8fc7\u5408\u5e76\u9884\u5370\u672c\u548c\u6700\u7ec8\u7248\u672c\u6765\u6574\u5408\u5f15\u7528\u3002\u800c Google Scholar \u5219\u8bd5\u56fe\u5bf9\u6240\u6709\u7248\u672c\u8fdb\u884c\u5206\u7ec4\uff0c\u6c47\u603b\u5176\u5f15\u7528\u3002<\/p>\n

\u7814\u7a76\u8f6f\u4ef6<\/strong><\/p>\n

\u6709\u4e9b\u8bba\u6587\u7684\u9ad8\u5f15\u7528\u5e76\u975e\u5076\u7136\uff0c\u800c\u662f\u6709\u610f\u8bc6\u4e3a\u7814\u7a76\u4eba\u5458\u63d0\u4f9b\u53ef\u5f15\u7528\u7684\u5bf9\u8c61<\/strong>\u3002\u4f8b\u5982\uff0c\u7ea6 25 \u5e74\u524d\uff0c\u836f\u5b66\u79d1\u5b66\u5bb6 Thomas Schmittgen \u64b0\u5199\u4e86\u4e00\u7bc7\u5173\u4e8e\u5b9a\u91cf PCR\uff08\u805a\u5408\u9176\u94fe\u5f0f\u53cd\u5e94\uff09\u6280\u672f\u7684\u8bba\u6587\u3002\u8be5\u6280\u672f\u7528\u4e8e\u5b9a\u91cf\u5206\u6790\u6837\u672c\u4e2d\u7684 DNA \u542b\u91cf\u3002Schmittgen \u539f\u672c\u5f15\u7528\u4e86\u6280\u672f\u624b\u518c\u4e2d\u7684\u516c\u5f0f\u5206\u6790\u6570\u636e\uff0c\u4f46\u5ba1\u7a3f\u4eba\u53cd\u9988\u79f0\u7528\u6237\u624b\u518c\u4e0d\u53ef\u4f5c\u4e3a\u5f15\u7528\u6765\u6e90\u3002\u56e0\u6b64\uff0c\u4ed6\u8054\u7cfb\u4e86\u516c\u5f0f\u7684\u521b\u4f5c\u8005\uff0c\u5171\u540c\u53d1\u8868\u4e86\u4e00\u7bc7\u5177\u6709\u5f15\u7528\u6027\u8d28\u7684\u8bba\u6587\u3002<\/p>\n

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\u53c2\u8003\u94fe\u63a5\uff1ahttps:\/\/www.nature.com\/articles\/d41586-025-01125-9<\/sup><\/p>\n

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