{"id":62173,"date":"2025-04-08T15:49:40","date_gmt":"2025-04-08T15:49:40","guid":{"rendered":""},"modified":"2025-04-08T15:49:40","modified_gmt":"2025-04-08T15:49:40","slug":"%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62173","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62173\/","title":{"rendered":"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u062e\u0635\u06cc\u0635 \u0645\u0646\u0627\u0628\u0639 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 DRL \u0628\u0631\u0627\u06cc \u062a\u0627\u0631\u06cc\u06a9\u06cc \u0645\u0642\u0627\u0648\u0645\u062a \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u062d\u0631\u06a9\u0627\u062a \u062e\u0648\u062f \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u062f\u0631\u0627\u0644 \u0641\u062f\u0631\u0627\u0644 \u062f\u0631 IOV"},"content":{"rendered":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nDRL-Based Resource Allocation for Motion Blur Resistant Federated Self-Supervised Learning in IoV<\/td>\n<\/tr>\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u062e\u0635\u06cc\u0635 \u0645\u0646\u0627\u0628\u0639 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 DRL \u0628\u0631\u0627\u06cc \u062a\u0627\u0631\u06cc\u06a9\u06cc \u0645\u0642\u0627\u0648\u0645\u062a \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u062d\u0631\u06a9\u0627\u062a \u062e\u0648\u062f \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u062f\u0631\u0627\u0644 \u0641\u062f\u0631\u0627\u0644 \u062f\u0631 IOV<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\nXueying Gu, Qiong Wu, Pingyi Fan, Qiang Fan, Nan Cheng, Wen Chen, Khaled B. Letaief<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nPDF<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u062a\u062d\u0648\u06cc\u0644\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u062a\u0631\u062c\u0645\u0647 \u0634\u062f\u0647 <\/td>\n\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\n<\/tr>\n
\u0646\u062d\u0648\u0647 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 <\/td>\n\u062f\u0648 \u062a\u0627 \u0633\u0647 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634 (\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc)<\/td>\n<\/tr>\n
\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n17<\/td>\n<\/tr>\n
\u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n\u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647<\/a><\/td>\n<\/tr>\n
\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a <\/td>\nComputer Vision and Pattern Recognition,Machine Learning,Networking and Internet Architecture,\u0686\u0634\u0645 \u0627\u0646\u062f\u0627\u0632 \u0631\u0627\u06cc\u0627\u0646\u0647 \u0648 \u062a\u0634\u062e\u06cc\u0635 \u0627\u0644\u06af\u0648\u06cc , \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 , \u0634\u0628\u06a9\u0647 \u0648 \u0645\u0639\u0645\u0627\u0631\u06cc \u0627\u06cc\u0646\u062a\u0631\u0646\u062a ,<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a <\/td>\nSubmitted 17 August, 2024; originally announced August 2024. , Comments: This paper has been submitted to IEEE Journal. The source code has been released at: https:\/\/github.com\/qiongwu86\/DRL-BFSSL<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 17 \u0627\u0648\u062a 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0627\u0648\u062a 2024 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f. \u060c \u0646\u0638\u0631\u0627\u062a: \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0645\u062c\u0644\u0647 IEEE \u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 \u0627\u0633\u062a.\u06a9\u062f \u0645\u0646\u0628\u0639 \u062f\u0631: https:\/\/github.com\/qiongwu86\/drl-bfssl \u0645\u0646\u062a\u0634\u0631 \u0634\u062f\u0647 \u0627\u0633\u062a<\/td>\n<\/tr>\n
\u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0647\u0627\u06cc \u0639\u0644\u0645\u06cc <\/td>\n\n INSPIRE HEP<\/a>
\n
\n NASA ADS<\/a>
\n
\n Google Scholar<\/a>
\n
\n Semantic Scholar<\/a>
\n
\n arXiv<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \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.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n

\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n

In the Internet of Vehicles (IoV), Federated Learning (FL) provides a privacy-preserving solution by aggregating local models without sharing data. Traditional supervised learning requires image data with labels, but data labeling involves significant manual effort. Federated Self-Supervised Learning (FSSL) utilizes Self-Supervised Learning (SSL) for local training in FL, eliminating the need for labels while protecting privacy. Compared to other SSL methods, Momentum Contrast (MoCo) reduces the demand for computing resources and storage space by creating a dictionary. However, using MoCo in FSSL requires uploading the local dictionary from vehicles to Base Station (BS), which poses a risk of privacy leakage. Simplified Contrast (SimCo) addresses the privacy leakage issue in MoCo-based FSSL by using dual temperature instead of a dictionary to control sample distribution. Additionally, considering the negative impact of motion blur on model aggregation, and based on SimCo, we propose a motion blur-resistant FSSL method, referred to as BFSSL. Furthermore, we address energy consumption and delay in the BFSSL process by proposing a Deep Reinforcement Learning (DRL)-based resource allocation scheme, called DRL-BFSSL. In this scheme, BS allocates the Central Processing Unit (CPU) frequency and transmission power of vehicles to minimize energy consumption and latency, while aggregating received models based on the motion blur level. Simulation results validate the effectiveness of our proposed aggregation and resource allocation methods.<\/p>\n

\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

\u062f\u0631 \u0627\u06cc\u0646\u062a\u0631\u0646\u062a \u0648\u0633\u0627\u06cc\u0644 \u0646\u0642\u0644\u06cc\u0647 (IOV) \u060c \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u062f\u0631\u0627\u0644 (FL) \u0628\u0627 \u062c\u0645\u0639 \u06a9\u0631\u062f\u0646 \u0645\u062f\u0644\u0647\u0627\u06cc \u0645\u062d\u0644\u06cc \u0628\u062f\u0648\u0646 \u0628\u0647 \u0627\u0634\u062a\u0631\u0627\u06a9 \u06af\u0630\u0627\u0631\u06cc \u062f\u0627\u062f\u0647 \u060c \u06cc\u06a9 \u0631\u0627\u0647 \u062d\u0644 \u062d\u0641\u0638 \u062d\u0631\u06cc\u0645 \u062e\u0635\u0648\u0635\u06cc \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u062f\u0647\u062f.\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062a\u062d\u062a \u0646\u0638\u0627\u0631\u062a \u0633\u0646\u062a\u06cc \u0646\u06cc\u0627\u0632 \u0628\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062a\u0635\u0648\u06cc\u0631 \u0628\u0627 \u0628\u0631\u0686\u0633\u0628 \u0647\u0627 \u062f\u0627\u0631\u062f \u060c \u0627\u0645\u0627 \u0628\u0631\u0686\u0633\u0628 \u0632\u062f\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0634\u0627\u0645\u0644 \u062a\u0644\u0627\u0634 \u062f\u0633\u062a\u06cc \u0642\u0627\u0628\u0644 \u062a\u0648\u062c\u0647\u06cc \u0627\u0633\u062a.\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u062f\u0631\u0627\u0633\u06cc\u0648\u0646 \u062e\u0648\u062f \u062a\u062d\u062a \u0646\u0638\u0627\u0631\u062a (FSSL) \u0627\u0632 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062e\u0648\u062f \u062a\u062d\u062a \u0646\u0638\u0627\u0631\u062a (SSL) \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0645\u062d\u0644\u06cc \u062f\u0631 FL \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0636\u0645\u0646 \u0645\u062d\u0627\u0641\u0638\u062a \u0627\u0632 \u062d\u0631\u06cc\u0645 \u062e\u0635\u0648\u0635\u06cc \u060c \u0646\u06cc\u0627\u0632 \u0628\u0647 \u0628\u0631\u0686\u0633\u0628 \u0647\u0627 \u0631\u0627 \u0627\u0632 \u0628\u06cc\u0646 \u0645\u06cc \u0628\u0631\u062f.\u062f\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0628\u0627 \u0633\u0627\u06cc\u0631 \u0631\u0648\u0634\u0647\u0627\u06cc SSL \u060c \u06a9\u0646\u062a\u0631\u0627\u0633\u062a \u062d\u0631\u06a9\u062a (MOCO) \u0628\u0627 \u0627\u06cc\u062c\u0627\u062f \u06cc\u06a9 \u0641\u0631\u0647\u0646\u06af \u0644\u063a\u062a \u060c \u062a\u0642\u0627\u0636\u0627\u06cc \u0645\u0646\u0627\u0628\u0639 \u0645\u062d\u0627\u0633\u0628\u0627\u062a\u06cc \u0648 \u0641\u0636\u0627\u06cc \u0630\u062e\u06cc\u0631\u0647 \u0633\u0627\u0632\u06cc \u0631\u0627 \u06a9\u0627\u0647\u0634 \u0645\u06cc \u062f\u0647\u062f.\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644 \u060c \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 MOCO \u062f\u0631 FSSL \u0646\u06cc\u0627\u0632 \u0628\u0647 \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u0641\u0631\u0647\u0646\u06af \u0644\u063a\u062a \u0645\u062d\u0644\u06cc \u0627\u0632 \u0648\u0633\u0627\u06cc\u0644 \u0646\u0642\u0644\u06cc\u0647 \u0628\u0647 \u0627\u06cc\u0633\u062a\u06af\u0627\u0647 \u067e\u0627\u06cc\u0647 (BS) \u062f\u0627\u0631\u062f \u060c \u06a9\u0647 \u062e\u0637\u0631 \u0646\u0634\u062a \u062d\u0631\u06cc\u0645 \u062e\u0635\u0648\u0635\u06cc \u0631\u0627 \u0628\u0647 \u0647\u0645\u0631\u0627\u0647 \u062f\u0627\u0631\u062f.\u06a9\u0646\u062a\u0631\u0627\u0633\u062a \u0633\u0627\u062f\u0647 (SIMCO) \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062f\u0645\u0627\u06cc \u062f\u0648\u06af\u0627\u0646\u0647 \u0628\u0647 \u062c\u0627\u06cc \u0641\u0631\u0647\u0646\u06af \u0644\u063a\u062a \u0628\u0631\u0627\u06cc \u06a9\u0646\u062a\u0631\u0644 \u062a\u0648\u0632\u06cc\u0639 \u0646\u0645\u0648\u0646\u0647 \u060c \u0645\u0633\u0626\u0644\u0647 \u0646\u0634\u062a \u062d\u0631\u06cc\u0645 \u062e\u0635\u0648\u0635\u06cc \u062f\u0631 FSSL \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 MOCO \u0631\u0627 \u0628\u0631\u0637\u0631\u0641 \u0645\u06cc \u06a9\u0646\u062f.\u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646 \u060c \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u062a\u0623\u062b\u06cc\u0631 \u0645\u0646\u0641\u06cc \u062a\u0627\u0631\u06cc \u062d\u0631\u06a9\u062a\u06cc \u0628\u0631 \u062a\u062c\u0645\u0639 \u0645\u062f\u0644 \u060c \u0648 \u0628\u0631 \u0627\u0633\u0627\u0633 SIMCO \u060c \u0645\u0627 \u06cc\u06a9 \u0631\u0648\u0634 FSSL \u0645\u0642\u0627\u0648\u0645 \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u062d\u0631\u06a9\u0627\u062a \u0631\u0627 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u060c \u06a9\u0647 \u0628\u0647 \u0622\u0646 BFSSL \u06af\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u062f.\u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646 \u060c \u0645\u0627 \u0628\u0627 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f \u06cc\u06a9 \u0637\u0631\u062d \u062a\u062e\u0635\u06cc\u0635 \u0645\u0646\u0627\u0628\u0639 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 (DRL) \u060c \u0628\u0647 \u0646\u0627\u0645 DRL-BFSSL \u060c \u0628\u0647 \u0645\u0635\u0631\u0641 \u0627\u0646\u0631\u0698\u06cc \u0648 \u062a\u0623\u062e\u06cc\u0631 \u062f\u0631 \u0641\u0631\u0622\u06cc\u0646\u062f BFSSL \u0645\u06cc \u067e\u0631\u062f\u0627\u0632\u06cc\u0645.\u062f\u0631 \u0627\u06cc\u0646 \u0637\u0631\u062d \u060c BS \u0641\u0631\u06a9\u0627\u0646\u0633 \u0648\u0627\u062d\u062f \u067e\u0631\u062f\u0627\u0632\u0634 \u0645\u0631\u06a9\u0632\u06cc (CPU) \u0648 \u0642\u062f\u0631\u062a \u0627\u0646\u062a\u0642\u0627\u0644 \u0648\u0633\u0627\u06cc\u0644 \u0646\u0642\u0644\u06cc\u0647 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0628\u0647 \u062d\u062f\u0627\u0642\u0644 \u0631\u0633\u0627\u0646\u062f\u0646 \u0645\u0635\u0631\u0641 \u0627\u0646\u0631\u0698\u06cc \u0648 \u062a\u0623\u062e\u06cc\u0631 \u0627\u062e\u062a\u0635\u0627\u0635 \u0645\u06cc \u062f\u0647\u062f \u060c \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 \u062c\u0645\u0639 \u0622\u0648\u0631\u06cc \u0645\u062f\u0644 \u0647\u0627\u06cc \u062f\u0631\u06cc\u0627\u0641\u062a \u0634\u062f\u0647 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0633\u0637\u062d \u062a\u0627\u0631\u06cc \u062d\u0631\u06a9\u062a\u06cc.\u0646\u062a\u0627\u06cc\u062c \u0634\u0628\u06cc\u0647 \u0633\u0627\u0632\u06cc \u060c \u0627\u062b\u0631\u0628\u062e\u0634\u06cc \u0631\u0648\u0634\u0647\u0627\u06cc \u062c\u0645\u0639 \u0622\u0648\u0631\u06cc \u0648 \u062a\u062e\u0635\u06cc\u0635 \u0645\u0646\u0627\u0628\u0639 \u0645\u0627 \u0631\u0627 \u062a\u0623\u06cc\u06cc\u062f \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \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.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n","protected":false},"excerpt":{"rendered":"

\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc DRL-Based Resource Allocation for Motion Blur Resistant Federated Self-Supervised Learning in IoV \u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc […]<\/p>\n","protected":false},"featured_media":27,"comment_status":"open","ping_status":"open","template":"","meta":{"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}}},"product_cat":[21],"product_tag":[],"class_list":{"0":"post-62173","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-21","7":"pmpro-has-access","8":"desktop-align-left","9":"tablet-align-left","10":"mobile-align-left","12":"first","13":"instock","14":"downloadable","15":"shipping-taxable","16":"purchasable","17":"product-type-simple"},"yoast_head":"\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u062e\u0635\u06cc\u0635 \u0645\u0646\u0627\u0628\u0639 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 DRL \u0628\u0631\u0627\u06cc \u062a\u0627\u0631\u06cc\u06a9\u06cc \u0645\u0642\u0627\u0648\u0645\u062a \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u062d\u0631\u06a9\u0627\u062a \u062e\u0648\u062f \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u062f\u0631\u0627\u0644 \u0641\u062f\u0631\u0627\u0644 \u062f\u0631 IOV - \u0641\u0631\u0648\u0634\u06af\u0627\u0647 \u0627\u06a9\u0633\u067e\u0631\u0633<\/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:\/\/express24.ir\/d\/product\/\u062a\u0631\u062c\u0645\u0647-\u0641\u0627\u0631\u0633\u06cc-\u0645\u0642\u0627\u0644\u0647-62173\/\" \/>\n<meta property=\"og:locale\" content=\"fa_IR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u062e\u0635\u06cc\u0635 \u0645\u0646\u0627\u0628\u0639 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 DRL \u0628\u0631\u0627\u06cc \u062a\u0627\u0631\u06cc\u06a9\u06cc \u0645\u0642\u0627\u0648\u0645\u062a \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u062d\u0631\u06a9\u0627\u062a \u062e\u0648\u062f \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u062f\u0631\u0627\u0644 \u0641\u062f\u0631\u0627\u0644 \u062f\u0631 IOV - 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