Tsinghua Science and Technology最新文献_第5页

Sphere Decoding for Binary Polar Codes with the Modified Multiplicative Repetition Construction 基于改进的乘式重复结构的二元极码球面译码

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010030

Haiqiang Chen;Yuanbo Liu;Shuping Dang;Qingnian Li;Youming Sun;Xiangcheng Li

{"title":"Sphere Decoding for Binary Polar Codes with the Modified Multiplicative Repetition Construction","authors":"Haiqiang Chen;Yuanbo Liu;Shuping Dang;Qingnian Li;Youming Sun;Xiangcheng Li","doi":"10.26599/TST.2024.9010030","DOIUrl":"https://doi.org/10.26599/TST.2024.9010030","url":null,"abstract":"Compared to the successive cancellation (SC)-based decoding algorithms, the sphere decoding (SD) algorithm can achieve better performance with reduced computational complexity, especially for short polar codes. In this paper, we propose a new method to construct the binary polar codes with the modified multiplicative repetition (MR)-based matrix. Different from the original construction, we first design a \u0000<tex>$2times 2 qtext{-ary}$</tex>\u0000 kernel to guarantee the single-level polarization effect. Then, by replacing the new-designed binary companion matrix, a novel strategy is further developed to enhance the polarization in the bit level, resulting in a better distance property. Finally, the SD-based Monte-Carlo (SDMC) method is used to construct MR-based binary polar codes, while the resulting codes without the butterfly pattern are decoded by the SD algorithm. Simulation results show that the proposed method with the SD algorithm can achieve a maximum performance gain of 0.27 dB compared to the original method with slightly lower complexity.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1229-1236"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817720","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks 基于深度学习的5G移动设备侧信道攻击安全检测

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010123

Amjed A. Ahmed;Mohammad Kamrul Hasan;Ali Alqahtani;Shayla Islam;Bishwajeet Pandey;Leila Rzayeva;Huda Saleh Abbas;Azana Hafizah Mohd Aman;Nayef Alqahtani

{"title":"Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks","authors":"Amjed A. Ahmed;Mohammad Kamrul Hasan;Ali Alqahtani;Shayla Islam;Bishwajeet Pandey;Leila Rzayeva;Huda Saleh Abbas;Azana Hafizah Mohd Aman;Nayef Alqahtani","doi":"10.26599/TST.2024.9010123","DOIUrl":"https://doi.org/10.26599/TST.2024.9010123","url":null,"abstract":"Mobile devices within Fifth Generation (5G) networks, typically equipped with Android systems, serve as a bridge to connect digital gadgets such as global positioning system, mobile devices, and wireless routers, which are vital in facilitating end-user communication requirements. However, the security of Android systems has been challenged by the sensitive data involved, leading to vulnerabilities in mobile devices used in 5G networks. These vulnerabilities expose mobile devices to cyber-attacks, primarily resulting from security gaps. Zero-permission apps in Android can exploit these channels to access sensitive information, including user identities, login credentials, and geolocation data. One such attack leverages “zero-permission” sensors like accelerometers and gyroscopes, enabling attackers to gather information about the smartphone's user. This underscores the importance of fortifying mobile devices against potential future attacks. Our research focuses on a new recurrent neural network prediction model, which has proved highly effective for detecting side-channel attacks in mobile devices in 5G networks. We conducted state-of-the-art comparative studies to validate our experimental approach. The results demonstrate that even a small amount of training data can accurately recognize 37.5% of previously unseen user-typed words. Moreover, our tap detection mechanism achieves a 92% accuracy rate, a crucial factor for text inference. These findings have significant practical implications, as they reinforce mobile device security in 5G networks, enhancing user privacy, and data protection.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1012-1026"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817772","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Dwell Scheduling Based on Dual-Side Time Pointers for Simultaneous Multi-Beam Radar 基于双面时间指针的多波束雷达自适应驻留调度

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2023.9010161

Siyu Heng;Ting Cheng;Jiaming Song;Zishu He;Luqing Liu;Yuanqing Wang

{"title":"Adaptive Dwell Scheduling Based on Dual-Side Time Pointers for Simultaneous Multi-Beam Radar","authors":"Siyu Heng;Ting Cheng;Jiaming Song;Zishu He;Luqing Liu;Yuanqing Wang","doi":"10.26599/TST.2023.9010161","DOIUrl":"https://doi.org/10.26599/TST.2023.9010161","url":null,"abstract":"Adaptive dwell scheduling is essential to achieve full performance for a simultaneous multi-beam radar system. The dwell scheduling for such a radar system considering desired execution time criterion is studied in this paper. The primary objective of this model is to achieve maximum scheduling gain and minimum scheduling cost while adhering to not only time, aperture, and frequency constraints, but also electromagnetic compatibility (EMC) constraint. The dwell scheduling algorithm is proposed to solve the above optimization problem, where several separation points are set on the timeline, so that each separator divides the scheduling interval into two sides. For the two sides, the dual-side time pointers are introduced, which move from the separator to both ends of the scheduling interval. The dwell tasks are analyzed in sequence at each analysis point based on their two-level synthetical priority. These tasks are then executed simultaneously by sharing the whole aperture under various constraints to accomplish multiple tasks concurrently. The above process is respectively conducted at each separator, and the final scheduling result is the one with the minimal cost among all. Simulation results prove that the proposed algorithm can achieve real-time dwell scheduling and outperform the existing algorithms in terms of scheduling performance.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1190-1200"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817723","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Integrated Blockchain Framework for Secure Data Sharing in IoT Fog Computing 物联网雾计算中安全数据共享的集成区块链框架

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010082

Peda Narayana Bathula;M. Sreenivasulu

{"title":"An Integrated Blockchain Framework for Secure Data Sharing in IoT Fog Computing","authors":"Peda Narayana Bathula;M. Sreenivasulu","doi":"10.26599/TST.2024.9010082","DOIUrl":"https://doi.org/10.26599/TST.2024.9010082","url":null,"abstract":"The importance of secure data sharing in fog computing is increasing due to the growing number of Internet of Things (IoT) devices. This article addresses the privacy and security issues brought up by data sharing in the context of IoT fog computing. The suggested framework, called “BlocFogSec”, secures key management and data sharing through blockchain consensus and smart contracts. Unlike existing solutions, BlocFogSec utilizes two types of smart contracts for secure key exchange and data sharing, while employing a consensus protocol to validate transactions and maintain blockchain integrity. To process and store data effectively at the network edge, the framework makes use of fog computing, notably reducing latency and raising throughput. BlocFogSec successfully blocks unauthorized access and data breaches by restricting transactions to authorized nodes. In addition, the framework uses a consensus protocol to validate and add transactions to the blockchain, guaranteeing data accuracy and immutability. To compare BlocFogSec's performance to that of other models, a number of simulations are conducted. The simulation results indicate that BlocFogSec consistently outperforms existing models, such as Security Services for Fog Computing (SSFC) and Blockchain-based Key Management Scheme (BKMS), in terms of throughput (up to 5135 bytes per second), latency (as low as 7 ms), and resource utilization (70% to 92%). The evaluation also takes into account attack defending accuracy (up to 100%), precision (up to 100%), and recall (up to 99.6%), demonstrating BlocFogSec's effectiveness in identifying and preventing potential attacks.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"957-977"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817699","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Efficient Quantum Enabled Machine Algorithm by Universal Features for Predicting Botnet Attacks in Digital Twin Enabled IoT Networks 基于通用特征的高效量子机器算法用于预测数字孪生物联网中僵尸网络攻击

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010052

Katta Rajesh Babu;Naramula Venkatesh;K. Shashidhar;Yellampalli Dasaratha Rami Reddy;K. Naga Prakash

{"title":"An Efficient Quantum Enabled Machine Algorithm by Universal Features for Predicting Botnet Attacks in Digital Twin Enabled IoT Networks","authors":"Katta Rajesh Babu;Naramula Venkatesh;K. Shashidhar;Yellampalli Dasaratha Rami Reddy;K. Naga Prakash","doi":"10.26599/TST.2024.9010052","DOIUrl":"https://doi.org/10.26599/TST.2024.9010052","url":null,"abstract":"In this manuscript, the authors introduce a quantum enabled Reinforcement Algorithm by Universal Features (REMF) as a lightweight solution designed to identify and assess the impact of botnet attacks on 5G Internet of Things (IoT) networks. REMF's primary objective is the swift detection of botnet assaults and their effects, aiming to prevent the initiation of such attacks. The algorithm introduces a novel adaptive classification boosting through reinforcement learning, training on values derived from universal features extracted from network transactions within a given training corpus. During the prediction phase, REMF assesses the Botnet attack confidence of feature values obtained from unlabeled network transactions. It then compares these botnet attack confidence values with the botnet attack confidence of optimal features derived during the training phase to predict the potential impact of the botnet attack, categorizing it as high, moderate, low, or not-an-attack (normal). The performance evaluation results demonstrate that REMF achieves the highest decision accuracy, displaying maximum sensitivity and specificity in predicting the scope of botnet attacks at an early stage. The experimental study illustrates that REMF outperforms existing detection techniques for predicting botnet attacks.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"947-956"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817765","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention 基于双域特征融合和补丁级关注的小镜头目标检测

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010031

Guangli Ren;Jierui Liu;Mengyao Wang;Peiyu Guan;Zhiqiang Cao;Junzhi Yu

{"title":"Few-Shot Object Detection via Dual-Domain Feature Fusion and Patch-Level Attention","authors":"Guangli Ren;Jierui Liu;Mengyao Wang;Peiyu Guan;Zhiqiang Cao;Junzhi Yu","doi":"10.26599/TST.2024.9010031","DOIUrl":"https://doi.org/10.26599/TST.2024.9010031","url":null,"abstract":"Few-shot object detection receives much attention with the ability to detect novel class objects using limited annotated data. The transfer learning-based solution becomes popular due to its simple training with good accuracy, however, it is still challenging to enrich the feature diversity during the training process. And fine-grained features are also insufficient for novel class detection. To deal with the problems, this paper proposes a novel few-shot object detection method based on dual-domain feature fusion and patch-level attention. Upon original base domain, an elementary domain with more category-agnostic features is superposed to construct a two-stream backbone, which benefits to enrich the feature diversity. To better integrate various features, a dual-domain feature fusion is designed, where the feature pairs with the same size are complementarily fused to extract more discriminative features. Moreover, a patch-wise feature refinement termed as patch-level attention is presented to mine internal relations among the patches, which enhances the adaptability to novel classes. In addition, a weighted classification loss is given to assist the fine-tuning of the classifier by combining extra features from FPN of the base training model. In this way, the few-shot detection quality to novel class objects is improved. Experiments on PASCAL VOC and MS COCO datasets verify the effectiveness of the method.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1237-1250"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817768","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain-Driven Secure Data Sharing Framework for Edge Computing Networks 边缘计算网络中区块链驱动的安全数据共享框架

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010051

Fuad A. M. Al-Yarimi;Ramzi Salah;Khaled Mohamoud

{"title":"Blockchain-Driven Secure Data Sharing Framework for Edge Computing Networks","authors":"Fuad A. M. Al-Yarimi;Ramzi Salah;Khaled Mohamoud","doi":"10.26599/TST.2024.9010051","DOIUrl":"https://doi.org/10.26599/TST.2024.9010051","url":null,"abstract":"This study examines secure and effective data sharing methods for edge computing networks. Traditional methods of sharing data at the edge have issues with security, speed, and consensus. The goal is to develop a Blockchain-based Secure Data Sharing Framework (BSDSF) capable of improving data integrity, latency, and overall network efficiency for edge-cloud computing applications. BSDSF proposes using blockchain technology with Byzantine Fault Tolerance (BFT) and smart contract-based validation as a new method of secure data sharing. It has a two-tiered consensus protocol to meet the needs of edge computing, which requires instantaneous responses. BSDSF employs Byzantine fault tolerance to deal with errors and protect against attacks. Smart contracts automate validation and consensus operations, while edge computing processes data at the attack site. Node validation and failure detection methods monitor network quality and dependability, while system security ensures secure communication between nodes. BSDSF is an important step toward digital freedom and trust by protecting security and improving transaction reliability. The framework demonstrates a reduction in transaction latency by up to 30% and an increase in throughput by 25% compared to traditional edge computing models, positioning BSDSF as a pivotal solution for fostering digital freedom and trust in edge computing environments.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"978-997"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817767","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Review on Air-Ground Coordination in Mobile Edge Computing: Key Technologies, Applications and Future Directions 移动边缘计算中地空协同：关键技术、应用及未来发展方向

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010142

Siqi Li;Guoqiang Liu;Li Li;Zhongyuan Zhang;Wenhao Fei;Haolong Xiang

{"title":"A Review on Air-Ground Coordination in Mobile Edge Computing: Key Technologies, Applications and Future Directions","authors":"Siqi Li;Guoqiang Liu;Li Li;Zhongyuan Zhang;Wenhao Fei;Haolong Xiang","doi":"10.26599/TST.2024.9010142","DOIUrl":"https://doi.org/10.26599/TST.2024.9010142","url":null,"abstract":"In recent years, Mobile Edge Computing (MEC) has received extensive research attention due to its characteristics, such as real-time data processing and flexible application deployment. However, traditional MEC server deployment relies on the terrestrial Base Stations (BSs), resulting in high deployment costs and limited coverage range. In response to these challenges, air-ground coordination has emerged, which effectively combines the advantages of edge computing and Unmanned Aerial Vehicles (UAVs), providing an effective architecture for edge intelligence. By utilizing the flexibility of UAVs and empowering them into edge nodes with computing resources, the coverage range of MEC can be expanded, thereby reducing the reliance of edge devices on terrestrial BSs. Furthermore, leveraging terrestrial BSs as supplements to the computing power compensates for relatively limited computational capabilities of UAVs. Although extensive studies have been conducted on air-ground coordination, there are few related summaries of application technologies and prospects. Thus, the key technologies of air-ground coordination and applications are comprehensively reviewed in this paper. Finally, to provide guidance for interested researchers, the development trends and potential applications of air-ground coordination are explored.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1359-1386"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817761","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MDGCN-Lt: Fair Web API Classification with Sparse and Heterogeneous Data Based on Deep GCN MDGCN-Lt：基于深度GCN的稀疏异构数据公平Web API分类

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010026

Boyuan Yan;Yankun Zhang;Wenwen Gong;Haoyang Wan;Wenwei Wang;Weiyi Zhong;Caixia Bu

{"title":"MDGCN-Lt: Fair Web API Classification with Sparse and Heterogeneous Data Based on Deep GCN","authors":"Boyuan Yan;Yankun Zhang;Wenwen Gong;Haoyang Wan;Wenwei Wang;Weiyi Zhong;Caixia Bu","doi":"10.26599/TST.2024.9010026","DOIUrl":"https://doi.org/10.26599/TST.2024.9010026","url":null,"abstract":"Developers integrate web Application Programming Interfaces (APIs) into edge applications, enabling data expansion to the edge computing area for comprehensive coverage of devices in that region. To develop edge applications, developers search API categories to select APIs that meet specific functionalities. Therefore, the accurate classification of APIs becomes critically important. However, existing approaches, as evident on platforms like programableweb.com, face significant challenges. Firstly, sparsity in API data reduces classification accuracy in works focusing on single-dimensional API information. Secondly, the multidimensional and heterogeneous structure of web APIs adds complexity to data mining tasks, requiring sophisticated techniques for effective integration and analysis of diverse data aspects. Lastly, the long-tailed distribution of API data introduces biases, compromising the fairness of classification efforts. Addressing these challenges, we propose MDGCN-Lt, an API classification approach offering flexibility in using multi-dimensional heterogeneous data. It tackles data sparsity through deep graph convolutional networks, exploring high-order feature interactions among API nodes. MDGCN-Lt employs a loss function with logit adjustment, enhancing efficiency in handling long-tail data scenarios. Empirical results affirm our approach's superiority over existing methods.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1294-1314"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817770","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DEFOG: Deep Learning with Attention Mechanism Enabled Cross-Age Face Recognition 深度学习与注意机制支持跨年龄人脸识别

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010107

Biaokai Zhu;Lu Li;Xiaochun Hu;Fulin Wu;Zhaojie Zhang;Shengnan Zhu;Yanxi Wang;Jiali Wu;Jie Song;Feng Li;Sanman Liu;Jumin Zhao

引用次数: 0