{"id":26499,"date":"2024-02-26T03:04:10","date_gmt":"2024-02-26T04:04:10","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/%d9%85%d9%82%d8%a7%d9%84%d9%87-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%aa%d8%ad%d9%88%d9%84-%d8%b4%d8%af%d9%87-%d9%85%d8%aa%d8%ad%d8%af-%d8%a8%d8%b1%d8%a7%db%8c-%d9%87%d9%88%d8%b4-%d9%85\/"},"modified":"2024-02-26T03:04:11","modified_gmt":"2024-02-26T04:04:11","slug":"%d9%85%d9%82%d8%a7%d9%84%d9%87-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%aa%d8%ad%d9%88%d9%84-%d8%b4%d8%af%d9%87-%d9%85%d8%aa%d8%ad%d8%af-%d8%a8%d8%b1%d8%a7%db%8c-%d9%87%d9%88%d8%b4-%d9%85","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d9%85%d9%82%d8%a7%d9%84%d9%87-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%aa%d8%ad%d9%88%d9%84-%d8%b4%d8%af%d9%87-%d9%85%d8%aa%d8%ad%d8%af-%d8%a8%d8%b1%d8%a7%db%8c-%d9%87%d9%88%d8%b4-%d9%85\/","title":{"rendered":"\u0645\u0642\u0627\u0644\u0647  \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u062a\u062d\u0648\u0644 \u0634\u062f\u0647 \u0645\u062a\u062d\u062f \u0628\u0631\u0627\u06cc \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0686\u0631\u062e\u0634\u06cc\u060c \u0627\u06cc\u0645\u0646 \u0648 \u06a9\u0648\u0686\u06a9"},"content":{"rendered":"<table class=\"table table-striped table-hover\">\n<tbody>\n<tr>\n<td>\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\n<td>Federated Transformed Learning for a Circular, Secure, and Tiny AI<\/td>\n<\/tr>\n<tr>\n<td>\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n<td>\u0645\u0642\u0627\u0644\u0647  \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u062a\u062d\u0648\u0644 \u0634\u062f\u0647 \u0645\u062a\u062d\u062f \u0628\u0631\u0627\u06cc \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0686\u0631\u062e\u0634\u06cc\u060c \u0627\u06cc\u0645\u0646 \u0648 \u06a9\u0648\u0686\u06a9<\/td>\n<\/tr>\n<tr>\n<td>\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\n<td>Weisi Guo, Schyler Sun, Bin Li, Sam Blakeman<\/td>\n<\/tr>\n<tr>\n<td>\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 <\/td>\n<td>\u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n<\/tr>\n<tr>\n<td>\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647: <\/td>\n<td>PDF<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n<td>7<\/td>\n<\/tr>\n<tr>\n<td>\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a  <\/td>\n<td>Networking and Internet Architecture,Artificial Intelligence,Machine Learning,\u0634\u0628\u06a9\u0647 \u0633\u0627\u0632\u06cc \u0648 \u0645\u0639\u0645\u0627\u0631\u06cc \u0627\u06cc\u0646\u062a\u0631\u0646\u062a , \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc , \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 ,<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0648\u0636\u06cc\u062d\u0627\u062a    <\/td>\n<td>Submitted 24 November, 2023; originally announced November 2023.<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc    <\/td>\n<td>\u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 24 \u0646\u0648\u0627\u0645\u0628\u0631 2023 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0646\u0648\u0627\u0645\u0628\u0631 2023 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n<p style=\"direction:ltr;\">Deep Learning (DL) is penetrating into a diverse range of mass mobility, smart living, and industrial applications, rapidly transforming the way we live and work. DL is at the heart of many AI implementations. A key set of challenges is to produce AI modules that are: (1) &#8220;circular&#8221; &#8211; can solve new tasks without forgetting how to solve previous ones, (2) &#8220;secure&#8221; &#8211; have immunity to adversarial data attacks, and (3) &#8220;tiny&#8221; &#8211; implementable in low power low cost embedded hardware. Clearly it is difficult to achieve all three aspects on a single horizontal layer of platforms, as the techniques require transformed deep representations that incur different computation and communication requirements. Here we set out the vision to achieve transformed DL representations across a 5G and Beyond networked architecture. We first detail the cross-sectoral motivations for each challenge area, before demonstrating recent advances in DL research that can achieve circular, secure, and tiny AI (CST-AI). Recognising the conflicting demand of each transformed deep representation, we federate their deep learning transformations and functionalities across the network to achieve connected run-time capabilities.<\/p>\n<h2>\u0686\u06a9\u06cc\u062f\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n<p>\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 (DL) \u062f\u0631 \u0637\u06cc\u0641 \u0645\u062a\u0646\u0648\u0639\u06cc \u0627\u0632 \u062a\u062d\u0631\u06a9 \u0627\u0646\u0628\u0648\u0647 \u060c \u0632\u0646\u062f\u06af\u06cc \u0647\u0648\u0634\u0645\u0646\u062f \u0648 \u06a9\u0627\u0631\u0628\u0631\u062f\u0647\u0627\u06cc \u0635\u0646\u0639\u062a\u06cc \u0646\u0641\u0648\u0630 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0628\u0647 \u0633\u0631\u0639\u062a \u0634\u06cc\u0648\u0647 \u0632\u0646\u062f\u06af\u06cc \u0648 \u06a9\u0627\u0631 \u0631\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u0645\u06cc \u062f\u0647\u062f.DL \u062f\u0631 \u0642\u0644\u0628 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0647\u0627\u06cc \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0642\u0631\u0627\u0631 \u062f\u0627\u0631\u062f.\u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u0635\u0644\u06cc \u0686\u0627\u0644\u0634 \u0647\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u0627\u0698\u0648\u0644 \u0647\u0627\u06cc AI \u0627\u0633\u062a \u06a9\u0647 \u0639\u0628\u0627\u0631\u062a\u0646\u062f \u0627\u0632: (1) &#8220;\u062f\u0627\u06cc\u0631\u0647 \u0627\u06cc&#8221; &#8211; \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u06a9\u0627\u0631\u0647\u0627\u06cc \u062c\u062f\u06cc\u062f \u0631\u0627 \u0628\u062f\u0648\u0646 \u0641\u0631\u0627\u0645\u0648\u0634 \u06a9\u0631\u062f\u0646 \u0646\u062d\u0648\u0647 \u062d\u0644 \u0645\u0648\u0627\u0631\u062f \u0642\u0628\u0644\u06cc \u060c (2) &#8220;\u0627\u06cc\u0645\u0646&#8221; &#8211; \u0627\u0632 \u0645\u0635\u0648\u0646\u06cc\u062a \u0627\u0632 \u062d\u0645\u0644\u0627\u062a \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u062a\u0646\u0627\u0642\u0636 \u0648 (3) \u062d\u0644 \u06a9\u0646\u062f.&#8221;Tiny&#8221; &#8211; \u0642\u0627\u0628\u0644 \u0627\u062c\u0631\u0627 \u062f\u0631 \u0633\u062e\u062a \u0627\u0641\u0632\u0627\u0631 \u062a\u0639\u0628\u06cc\u0647 \u0634\u062f\u0647 \u06a9\u0645 \u0647\u0632\u06cc\u0646\u0647 \u06a9\u0645.\u0628\u062f\u06cc\u0647\u06cc \u0627\u0633\u062a \u06a9\u0647 \u062f\u0633\u062a\u06cc\u0627\u0628\u06cc \u0628\u0647 \u0647\u0631 \u0633\u0647 \u062c\u0646\u0628\u0647 \u062f\u0631 \u06cc\u06a9 \u0644\u0627\u06cc\u0647 \u0627\u0641\u0642\u06cc \u0627\u0632 \u0633\u06cc\u0633\u062a\u0645 \u0639\u0627\u0645\u0644 \u0647\u0627 \u062f\u0634\u0648\u0627\u0631 \u0627\u0633\u062a \u060c \u0632\u06cc\u0631\u0627 \u0627\u06cc\u0646 \u062a\u06a9\u0646\u06cc\u06a9 \u0647\u0627 \u0628\u0647 \u0628\u0627\u0632\u0646\u0645\u0627\u06cc\u06cc \u0647\u0627\u06cc \u0639\u0645\u06cc\u0642 \u062a\u0628\u062f\u06cc\u0644 \u0634\u062f\u0647 \u0646\u06cc\u0627\u0632 \u062f\u0627\u0631\u0646\u062f \u06a9\u0647 \u0645\u062d\u0627\u0633\u0628\u0627\u062a \u0648 \u0646\u06cc\u0627\u0632\u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0631\u0627 \u0645\u062a\u062d\u0645\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f.\u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0645\u0627 \u0627\u06cc\u0646 \u0686\u0634\u0645 \u0627\u0646\u062f\u0627\u0632 \u0631\u0627 \u0628\u0631\u0627\u06cc \u062f\u0633\u062a\u06cc\u0627\u0628\u06cc \u0628\u0647 \u0628\u0627\u0632\u0646\u0645\u0627\u06cc\u06cc \u0647\u0627\u06cc DL \u062a\u0628\u062f\u06cc\u0644 \u0634\u062f\u0647 \u062f\u0631 \u06cc\u06a9 \u0645\u0639\u0645\u0627\u0631\u06cc 5G \u0648 \u0641\u0631\u0627\u062a\u0631 \u0627\u0632 \u0622\u0646 \u0628\u06cc\u0627\u0646 \u06a9\u0631\u062f\u06cc\u0645.\u0645\u0627 \u0627\u0628\u062a\u062f\u0627 \u0642\u0628\u0644 \u0627\u0632 \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0646 \u067e\u06cc\u0634\u0631\u0641\u062a \u0647\u0627\u06cc \u0627\u062e\u06cc\u0631 \u062f\u0631 \u062a\u062d\u0642\u06cc\u0642\u0627\u062a DL \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0647 AI \u062f\u0627\u06cc\u0631\u0647 \u0627\u06cc \u060c \u0627\u06cc\u0645\u0646 \u0648 \u0631\u06cc\u0632 (CST-AI) \u062f\u0633\u062a \u06cc\u0627\u0628\u062f \u060c \u0627\u0646\u06af\u06cc\u0632\u0647 \u0647\u0627\u06cc \u0645\u0642\u0637\u0639\u06cc \u0628\u0631\u0627\u06cc \u0647\u0631 \u0645\u0646\u0637\u0642\u0647 \u0686\u0627\u0644\u0634 \u0631\u0627 \u062a\u0648\u0636\u06cc\u062d \u0645\u06cc \u062f\u0647\u06cc\u0645.\u0628\u0627 \u0634\u0646\u0627\u062e\u062a \u062a\u0642\u0627\u0636\u0627\u06cc \u0645\u062a\u0646\u0627\u0642\u0636 \u0627\u0632 \u0647\u0631 \u0628\u0627\u0632\u0646\u0645\u0627\u06cc\u06cc \u0639\u0645\u06cc\u0642 \u060c \u0645\u0627 \u062a\u062d\u0648\u0644\u0627\u062a \u0648 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0622\u0646\u0647\u0627 \u0631\u0627 \u062f\u0631 \u0633\u0631\u0627\u0633\u0631 \u0634\u0628\u06a9\u0647 \u0641\u062f\u0627\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0628\u0647 \u0642\u0627\u0628\u0644\u06cc\u062a \u0647\u0627\u06cc \u0632\u0645\u0627\u0646 \u0627\u062c\u0631\u0627 \u0645\u062a\u0635\u0644 \u0628\u0631\u0633\u06cc\u0645.<\/p>\n<table class=\"table table-bordered table-primary\">\r\n<tr>\r\n\t<td>\r\n\t\u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0632\u0628\u0627\u0646 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc \u0627\u0633\u062a.\r\n\t<\/td>\r\n<\/tr>\r\n\t\r\n<tr>\r\n\t<td>\r\n     \u0628\u0631\u0627\u06cc \u0633\u0641\u0627\u0631\u0634 \u062a\u0631\u062c\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u06cc\u06a9\u06cc \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0645\u0627\u0633\u060c \u067e\u06cc\u0627\u0645\u06a9\u060c \u062a\u0644\u06af\u0631\u0627\u0645 \u0648 \u06cc\u0627 \u0648\u0627\u062a\u0633 \u0627\u067e \u0628\u0627 \u0634\u0645\u0627\u0631\u0647 \u0632\u06cc\u0631 \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f:\r\n\t<br \/><br \/>\r\n\t09395106248\r\n\t\t\r\n\t\t\r\n\t<br \/><br \/>\r\n\t\t\u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0634\u0631\u0627\u06cc\u0637 \u062a\u0631\u062c\u0645\u0647 \u0628\u0647 \u0635\u0648\u0631\u062a \u0632\u06cc\u0631 \u0627\u0633\u062a:\r\n\t\t<br \/>\r\n\t\t<ul>\r\n\t\t<li>\r\n\t\t\u0642\u06cc\u0645\u062a \u0647\u0631 \u0635\u0641\u062d\u0647 \u062a\u0631\u062c\u0645\u0647 \u062f\u0631 \u062d\u0627\u0644 \u062d\u0627\u0636\u0631 40 \u0647\u0632\u0627\u0631 \u062a\u0648\u0645\u0627\u0646 \u0645\u06cc \u0628\u0627\u0634\u062f. \r\n\t\t<\/li>\r\n\t\t<li>\r\n\t\t\u062a\u062d\u0648\u06cc\u0644 \u0645\u0642\u0627\u0644\u0647 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\u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.\r\n\t\t<\/li>\r\n\t\t<li>\r\n\t\t\u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.\r\n\t\t<\/li>\r\n\t<\/td>\r\n\t\r\n\t\r\n<\/tr>\r\n<\/table>\r\n\r\n\r\n\n","protected":false},"excerpt":{"rendered":"<p>\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc Federated Transformed Learning for a Circular, Secure, and Tiny AI \u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc 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