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GENERATIVE: 作品数：537被引量：766H指数：13; 导出分析报告; 相关作者：郝志桃王东李昌华李曙光赵凯华更多>>; 相关机构：华中师范大学浙江省交通规划设计研究院有限公司西安建筑科技大学上海电力大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金中国博士后科学基金国家社会科学基金高等学校学科创新引智计划更多>>

Intelligent integrated sensing and communication:a survey: 《Science China(Information Sciences)》2025年第3期1-42,共42页Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG; supported by National Natural Science Foundation of China(Grant Nos.U23A20271,62325103);Application and Fundamental Research Planning Project in Liaoning Province(Grant No.2023TH2/101300197)。; Integrated sensing and communication(ISAC)is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities.However,t...; 关键词：artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelli-gence integrated sensing and communication machine learning transfer learning

MetaCoorNet:an improved generated residual network for grasping pose estimation: 《Science China(Information Sciences)》2025年第3期238-253,共16页Hejia GAO Chuanfeng HE Junjie ZHAO Changyin SUN; supported in part by National Natural Science Foundation of China(Grant Nos.62388101,62303010);University Synergy Innovation Program of Anhui Province(Grant No.GXXT-2023-039);Anhui Provincial Key Research Program of Universities(Grant No.2022AH050087)。; Robotic grasping presents significant challenges due to variations in object properties,environmental complexities,and the demand for real-time operation.This study proposes the MetaCoorNet(MCN),which is a novel deep ...; 关键词：generative ResNet meta light block coordinate attention feature resolution robot grasping

Mitigate noisy data for smart IoT via GAN based machine unlearning: 《Science China(Information Sciences)》2024年第3期58-74,共17页Zhuo MA Yilong YANG Yang LIU Xinjing LIU Jianfeng MA; supported by National Key Research and Development Program of China (Grant No.2022YFB3103500);National Natural Science Foundation of China (Grant Nos.U21A20464,61872283);Natural Science Basic Research Program of Shaanxi (Grant No.2021JC-22);Key Research and Development Program of Shaanxi (Grant No.2022GY029);China 111 Project (Grant No.B16037)。; With the development of IoT applications,machine learning dramatically improves the utility of variable IoT systems such as autonomous driving.Although the pretrain-finetune framework can cope well with data heterogen...; 关键词：machine unlearning generative adversarial network out of distribution data Internet of Thing neural network

AtomGAN:unsupervised deep learning for fast and accurate defect detection of 2D materials at the atomic scale被引量：2: 《Science China(Information Sciences)》2023年第6期98-110,共13页Danpeng CHENG Wuxin SHA Zuo XU Shide LI Zhigao YIN Yuling LANG Shun TANG Yuan-Cheng CAO; supported by National Key R&D Program of China (Grant No.2022YFB2404303);National Natural Science Foundation of China (Grant Nos.52107224,52077096);State Grid Corporation of China (Grant No.520626210064);China Postdoctoral Science Foundation (Grant No.2019M662612)。; The extraction of atomic-level material features from electron microscope images is crucial for studying structure-property relationships and discovering new materials.However,traditional electron microscope analyses ...; 关键词：deep learning generative adversarial network defect detection atomic resolution 2D materials

Survey on leveraging pre-trained generative adversarial networks for image editing and restoration被引量：4: 《Science China(Information Sciences)》2023年第5期24-51,共28页Ming LIU Yuxiang WEI Xiaohe WU Wangmeng ZUO Lei ZHANG; supported by National Natural Science Foundation of China(Grant Nos.U19A2073,62006064);Hong Kong RGC RIF(Grant No.R5001-18);2020 Heilongjiang Provincial Natural Science Foundation Joint Guidance Project(Grant No.LH2020C001)。; Generative adversarial networks(GANs)have drawn enormous attention due to their simple yet efective training mechanism and superior image generation quality.With the ability to generate photorealistic high-resolution(...; 关键词：SURVEY generative adversarial networks pre-trained models image editing image restoration

BiTGAN:bilateral generative adversarial networks for Chinese ink wash painting style transfer: 《Science China(Information Sciences)》2023年第1期318-319,共2页Xiao HE Mingrui ZHU Nannan WANG Xiaoyu WANG Xinbo GAO; supported in part by National Key Research and Development Program of China (Grant No.2018AAA0103202);National Natural Science Foundation of China (Grant Nos.62106184,62036007,61922066,61876142,62176198)。; Dear editor,Chinese ink wash painting occupies a pivotal position in Chinese traditional painting and has high artistic value.It is meaningful to design a special automatic algorithm for Chinese ink wash painting styl...; 关键词：PAINTING meaningful EDITOR

VulnerGAN: a backdoor attack through vulnerability amplification against machine learning-based network intrusion detection systems: 《Science China(Information Sciences)》2022年第7期28-46,共19页Guangrui LIU Weizhe ZHANG Xinjie LI Kaisheng FAN Shui YU; supported in part by National Key Research and Development Program of China(Grant No.2020YFB1406902);Key-Area Research and Development Program of Guangdong Province(Grant No.2020B0101360001);Shenzhen Science and Technology Research and Development Foundation(Grant No.JCYJ20190806143418198);National Natural Science Foundation of China(Grant No.61872110);Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2021007);Peng Cheng Laboratory Project(Grant No.PCL2021A02)。; Machine learning-based network intrusion detection systems(ML-NIDS) are extensively used for network security against unknown attacks. Existing intrusion detection systems can effectively defend traditional network at...; 关键词：AI security adversarial sample data poisoning network intrusion detection generative adversarial network

Triple discriminator generative adversarial network for zero-shot image classification被引量：8: 《Science China(Information Sciences)》2021年第2期1-14,共14页Zhong JI Jiangtao YAN Qiang WANG Yanwei PANG Xuelong LI; supported by National Natural Science Foundation of China(Grant Nos.61771329,61632018)。; One key challenge in zero-shot classification(ZSC)is the exploration of knowledge hidden in unseen classes.Generative methods such as generative adversarial networks(GANs)are typically employed to generate the visual ...; 关键词：zero-shot classification generative adversarial nets text reconstruction Sharma-Mittal entropy

Learning efficient text-to-image synthesis via interstage cross-sample similarity distillation被引量：2: 《Science China(Information Sciences)》2021年第2期15-26,共12页Fengling MAO Bingpeng MA Hong CHANG Shiguang SHAN Xilin CHEN; supported in part by National Natural Science Foundation of China(Grant Nos.61876171,61976203);Fundamental Research Funds for the Central Universities。; For a given text,previous text-to-image synthesis methods commonly utilize a multistage generation model to produce images with high resolution in a coarse-to-fine manner.However,these methods ignore the interaction a...; 关键词：generative adversarial network(GAN) text-to-image synthesis knowledge distillation

Reciprocal translation between SAR and optical remote sensing images with cascaded-residual adversarial networks被引量：1: 《Science China(Information Sciences)》2021年第2期150-164,共15页Shilei FU Feng XU Ya-Qiu JIN; supported in part by National Key R&D Program of China(Grant No.2017YFB0502703);Natural Science Foundation of China(Grant Nos.61822107,61571134)。; Despite the advantages of all-weather and all-day high-resolution imaging,synthetic aperture radar(SAR)images are much less viewed and used by general people because human vision is not adapted to microwave scattering...; 关键词：synthetic aperture radar generative adversarial network(GAN) image translation cascaded residual connection Frechet inception distance

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