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检索条件"机构=Nanjing University of Science and Technology of Electrical and Computer Engineering"
66629 条 记 录,以下是1-10 订阅
排序:
Enhanced Acceleration for Generalized Nonconvex Low-Rank Matrix Learning
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Chinese Journal of Electronics 2025年 第1期34卷 98-113页
作者: Hengmin Zhang Jian Yang Wenli Du Bob Zhang Zhiyuan Zha Bihan Wen School of Electrical and Electronic Engineering Nanyang Technological University School of Computer Science and Engineering Nanjing University of Science and Technology School of Information Science and Engineering East China University of Science and Technology Department of Electrical and Computer Engineering University of Macau
Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inher... 详细信息
来源: 评论
SSA: semantic structure aware inference on CNN networks for weakly pixel-wise dense predictions without cost
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Frontiers of computer science 2025年 第2期19卷 1-10页
作者: Yanpeng SUN Zechao LI School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210014China
The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps(CAMs)to generate pseudo masks as ***,existing methods often incorporate trainable modules to expand the immature cl... 详细信息
来源: 评论
A recover-then-discriminate framework for robust anomaly detection
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science China(Information sciences) 2025年 第4期68卷 300-318页
作者: Peng XING Dong ZHANG Jinhui TANG Zechao LI School of Computer Science and Engineering Nanjing University of Science and Technology Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology
Anomaly detection(AD) has been extensively studied and applied across various scenarios in recent years. However, gaps remain between the current performance and the desired recognition accuracy required for practical... 详细信息
来源: 评论
APF-GAN:Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network
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Computational Visual Media 2024年 第1期10卷 187-192页
作者: Yuxuan Li Lingfeng Yang Xiang Li College of Computer Science Nankai UniversityTianjinChina School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingChina
The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent ***,there are still some limitations,including limited di... 详细信息
来源: 评论
Feature-Grounded Single-Stage Text-to-Image Generation
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Tsinghua science and technology 2024年 第2期29卷 469-480页
作者: Yuan Zhou Peng Wang Lei Xiang Haofeng Zhang School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing 210044China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China
Recently,Generative Adversarial Networks(GANs)have become the mainstream text-to-image(T2I)***,a standard normal distribution noise of inputs cannot provide sufficient information to synthesize an image that approache... 详细信息
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Augmented FCN: rethinking context modeling for semantic segmentation
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science China(Information sciences) 2023年 第4期66卷 193-211页
作者: Dong ZHANG Liyan ZHANG Jinhui TANG School of Computer Science and Engineering Nanjing University of Science and Technology College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics
The effectiveness of modeling contextual information has been empirically shown in numerous computer vision tasks. In this paper, we propose a simple yet efficient augmented fully convolutional network(AugFCN) by aggr... 详细信息
来源: 评论
YOLO-LFD: A Lightweight and Fast Model for Forest Fire Detection
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computers, Materials & Continua 2025年 第2期82卷 3399-3417页
作者: Honglin Wang Yangyang Zhang Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Electrical&Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA
Forest fires pose a serious threat to ecological balance, air quality, and the safety of both humans and wildlife. This paper presents an improved model based on You Only Look Once version 5 (YOLOv5), named YOLO Light... 详细信息
来源: 评论
Clustered Reinforcement Learning
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Frontiers of computer science 2025年 第4期19卷 43-57页
作者: Xiao MA Shen-Yi ZHAO Zhao-Heng YIN Wu-Jun LI National Key Laboratory for Novel Software Technology Department of Computer Science and TechnologyNanjing UniversityNanjing 210023China Department of Electrical Engineering and Computer Sciences University of CaliforniaBerkeleyCA 94720-1770USA
Exploration strategy design is a challenging problem in reinforcement learning(RL),especially when the environment contains a large state space or sparse *** exploration,the agent tries to discover unexplored(novel)ar... 详细信息
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A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration
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IEEE/CAA Journal of Automatica Sinica 2024年 第4期11卷 965-981页
作者: Yong-Chao Li Rui-Sheng Jia Ying-Xiang Hu Hong-Mei Sun the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590 the Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266000China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the College of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210000China
In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation *** this paper,we aim to reduce the annotation cost of crowd datasets,a... 详细信息
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Enhanced Multi-Scale Object Detection Algorithm for Foggy Traffic Scenarios
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computers, Materials & Continua 2025年 第2期82卷 2451-2474页
作者: Honglin Wang Zitong Shi Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China School of Electrical&Computer Engineering University of Illinois at Urbana ChampaignUrbanaIL 61801USA
In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scal... 详细信息
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