检索结果-内蒙古大学图书馆

DPNet: Dynamic Pooling network for Accurate and Efficient Size-Aware Tiny Object Detection

IEEE Internet of Things Journal 2025年

作者： Gong, Luqi Chen, Haotian Chen, Yikun Yao, Tianliang Li, Chao Zhao, Shuai Han, Guangjie Beijing University of Posts and Telecommunications School of Computer Science Beijing China Zhejiang Lab Research Center for Space Computing System Hangzhou China Southwest Jiaotong University SWJTU-LEEDS Joint School Chengdu China LTD Guangdong Zhiyun City construction Technology Co Zhuhai China Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education China

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging images significantly increases computational costs and the number of negative samples, severely degrading detection performance and limiting its applicability. This paper proposes a Dynamic Pooling network (DPNet) for tiny object detection to mitigate these issues. DPNet employs a flexible down-sampling strategy by introducing a factor (df) to relax the fixed down-sampling process of the feature map to an adjustable one. Furthermore, we design a lightweight predictor to predict df for each input image, which will be used to decrease the resolution of feature map in backbone. Thus, we achieve input-aware down-sampling. We design an Adaptive Normalization Module (ANM) to make a unified detector well compatible with different dfs. At the same time, we also design a guidance loss to supervise the predictor’s training. DPNet realizes the dynamic allocation of computing resources to trade off detection accuracy and efficiency through this. Experiments on the TinyCOCO and TinyPerson datasets show that our DPNet can save over 35% and 25% GFLOPs, respectively, while maintaining comparable detection *** code will be made publicly available. © 2014 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Influence of key Ecological Function Area Policy on the Components of Water Balance-A Case Study in Yangtze River Basin

SSRN

引用

SSRN 2025年

作者： You, Guangyong Xu, Yan Zhang, Minxia Gao, Yuanyun He, Honglin Zhang, Mengyu Liu, Bo Zhu, Minxin You, Juan Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment Jiangsu Nanjing210042 China Jiangsu Frontier Electric Power Technology Company Limited Jiangsu Nanjing211102 China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China National Ecosystem Science Data Center Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100190 China School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China Hebei Engineering Consulting Institute Hebei Shijiazhuang050057 China

The National key Ecological Function Area (KEFA) policy of China, the world's largest ecological compensation program, played an important role in improving the ecological functions. To reveal the effects of KEFA on land surface water balance components, this study analyzed the difference between KEFA area and the rest of the area (NKEF) in Yangtze River Basin (YRB). The results showed that, 1) the KEFA had higher interception loss (Ei) but lower actual evaporation (Ea) and transpiration (Et) than NKEF. The proportions of Ea, Et, Ei to precipitation (Pre) were higher in KEFA than NKEF, suggesting the KEFA had higher water consumption possibly resulting from the vegetation growth and dynamics. 2) Over the past decades, Ea, Et, and Ei, as well as their proportions to Precipitation (PRE), were significantly increased in YRB. A significant change point around the year 2000 coincided with the climate cycles periods and implementations of national ecological restoration programs i.e. National Grain for Green Program. 3) The long-term trends of Ea/Pre and the Ei/Pre were higher in KEFA than NKEF, especially for the post-2000 period. Compared with pre-2000 period, The Ea/Pre, Et/Pre of the NKEF in the post-2000 period displayed sharp decrease, suggesting the decreasing vegetation cover and water consumption. This study revealed the hydrological effects of KEFA policy, the findings are meaningful in evaluating and optimizing the KEFA policy. © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Linked List Encryption Scheme for Image Steganography without Embedding

引用

Computer Modeling in Engineering & sciences 2024年第10期141卷 331-352页

作者： Pengbiao Zhao Qi Zhong Jingxue Chen Xiaopei Wang Zhen Qin Erqiang Zhou Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu610054China Faculty of Data Science City University of MacaoMacao999078China Department of Computer Science and Engineering University of CaliforniaRiversideCA 92521USA

Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information *** enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover *** this paper,a novel encrypted communication scheme for image SWE is *** reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer *** employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be *** receiver can restore the secretmessage fromthe received image using only the list header position *** scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover *** boasts high concealment and security,along with a complete message restoration rate,making it resistant to ***,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of *** validate the proposed framework,practical tests and comparisons are conducted using multiple *** results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.

关键词： Steganography encryption steganography without embedding coverless steganography

来源：评论

学校读者我要写书评

暂无评论

User Profiling for CSDN:keyphrase Extraction,User Tagging and User Growth Value Prediction

引用

data Intelligence 2019年第2期1卷 137-159页

作者： Guoliang Xing Hao Gao Qi Cao Xinyu Yue Bingbing Xu Keting Cen Huawei Shen Key Laboratory of Network Data Science and Technology Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

The Chinese Software Developer network(CSDN)is one of the largest information technology communities and service platforms in *** paper describes the user profiling for CSDN,an evaluation track of SMP Cup *** contains three tasks:(1)user document keyphrase extraction,(2)user tagging and(3)user growth value *** the first task,we treat keyphrase extraction as a classification problem and train a Gradient-Boosting-Decision-Tree model with comprehensive *** the second task,to deal with class imbalance and capture the interdependency between classes,we propose a two-stage framework:(1)for each class,we train a binary classifier to model each class against all of the other classes independently;(2)we feed the output of the trained classifiers into a softmax classifier,tagging each user with multiple *** the third task,we propose a comprehensive architecture to predict user growth *** contributions in this paper are summarized as follows:(1)we extract various types of features to identify the key factors in user value growth;(2)we use the semi-supervised method and the stacking technique to extend labeled data sets and increase the generality of the trained model,resulting in an impressive performance in our *** the competition,we achieved the first place out of 329 teams.

关键词： User profiling keyphrase extraction User tagging Growth value prediction Word embedding

来源：评论

学校读者我要写书评

暂无评论

Semantic QoS Ontology and Semantic Service Ranking Approach for IoT services

引用

Journal of Harbin Institute of technology(New Series) 2014年第6期21卷 102-112页

作者： Nwe Nwe Htay Win Jian-Min Bao Gang Cui Purevsuren Dalaijargal School of Computer Science and Technology Harbin Institute of Technology Key Lab of Broadband Wireless Communication and Sensor Network Technolog Jiangsu Provincial Engineering Research Center of Telecommunications and Network TechnologyMinistry of Education

Due to a rapid increase in the number of functionally equivalent web services at open and dynamic Io T service environment,Qo S has become a major discrimination factor to reflect the user's expectation and experience of using a *** are different languages and models for expressing Qo S advertisements and requirements among service providers and ***,it leads to the issues of semantic interoperability of Qo S information and semantic similarity match between a semantic description of the service being requested by the service consumer,and a formal description of the service being offered by the service *** this paper,we propose a hierarchical two-layer semantic Qo S ontology to promote the description and declaration of Qo S-based service information in detail for any domain and ***,we develop a semantic matchmaking algorithm to compare the web services according to their Qo S information and adopt analytical hierarchy process( AHP) to make decision for the ranked services depending on the Qo S *** comparison study and experimental result show that our proposed system is superior to other service ranking approaches.

关键词： IoT service environment semantic QoS ontology semantic matchmaking algorithm QoS-based service information analytical hierarchy process

来源：评论

学校读者我要写书评

暂无评论

A Novel Identification Method for Frequently Switched Encrypted Video Streaming in Complex network Environment 22

A Novel Identification Method for Frequently Switched Encryp...

引用

2022 Asia Conference on Electrical, Power and Computer Engineering, EPCE 2022

作者： Zhang, Y.U. Ma, Xiaowei Leng, Dongpeng Yu, Peiran College of Cyber Science Nankai University Tianjin Key Laboratory of Network and Data Security Technology Tianjin China College of Computer Science Nankai University Tianjin Key Laboratory of Network and Data Security Technology Tianjin China

ISBN: (纸本)9781450396127

Nowadays, to provide stable video streaming and smooth user experience among different scenarios, more and more online video sharing and social media platforms adopt the Dynamic Adaptive Streaming over HTTP (DASH), which can transmit and play videos of appropriate quality levels according to the user's network conditions. For sake of illegal videos spreading on the platforms, the identification of encrypted DASH video streaming is of great importance. However, related works on the identification of encrypted DASH video streaming are seldom concerned with the streaming under poor network conditions that the video quality levels are switched relatively frequently. Therefore, we propose a novel video fingerprint extraction method as well as a novel multi-layer fuzzy matching scheme. So far as we know, we are the first to solve the identification of encrypted DASH video streaming under poor network conditions. And to reduce the overhead we establish a local video fingerprint database using the fingerprint extraction method. Our scheme can identify the encrypted DASH video streaming of frequently switched quality levels using very short-time network traffic sniffing. Experiments show that the time required for traffic sniffing is just 6 seconds and the accuracy exceeds 98%, which is significantly better than state-of-art methods. Besides, our scheme performs well on the identification of streaming in multiple scenarios. © 2022 ACM.

关键词： Video streaming

来源：评论

学校读者我要写书评

暂无评论

Nested Event Extraction upon Pivot Element Recognition 30

Nested Event Extraction upon Pivot Element Recognition

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Ren, Weicheng Li, Zixuan Jin, Xiaolong Bai, Long Su, Miao Liu, Yantao Guan, Saiping Guo, Jiafeng Cheng, Xueqi School of Computer Science and Technology University of Chinese Academy of Sciences China Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9782493814104

Nested Event Extraction (NEE) aims to extract complex event structures where an event contains other events as its arguments recursively. Nested events involve a kind of Pivot Elements (PEs) that simultaneously act as arguments of outer-nest events and as triggers of inner-nest events, and thus connect them into nested structures. This special characteristic of PEs brings challenges to existing NEE methods, as they cannot well cope with the dual identities of PEs. Therefore, this paper proposes a new model, called PerNee, which extracts nested events mainly based on recognizing PEs. Specifically, PerNee first recognizes the triggers of both inner-nest and outer-nest events and further recognizes the PEs via classifying the relation type between trigger pairs. The model uses prompt learning to incorporate information from both event types and argument roles for better trigger and argument representations to improve NEE performance. Since existing NEE datasets (e.g., Genia11) are limited to specific domains and contain a narrow range of event types with nested structures, we systematically categorize nested events in the generic domain and construct a new NEE dataset, called ACE2005-Nest. Experimental results demonstrate that PerNee consistently achieves state-of-the-art performance on ACE2005-Nest, Genia11, and Genia13. The ACE2005-Nest dataset and the code of the PerNee model are available at https://***/waysonren/PerNee. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

Important sampling based active learning for imbalance classification

引用

science China(Information sciences) 2020年第8期63卷 196-209页

作者： Xinyue WANG Bo LIU Siyu CAO Liping JING Jian YU School of Computer and Information Technology Beijing Jiaotong University Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University College of Information Science and Technology Hebei Agricultural University

Imbalance in data distribution hinders the learning performance of classifiers. To solve this problem, a popular type of methods is based on sampling(including oversampling for minority class and undersampling for majority class) so that the imbalanced data becomes relatively balanced data. However,they usually focus on one sampling technique, oversampling or undersampling. Such strategy makes the existing methods suffer from the large imbalance ratio(the majority instances size over the minority instances size). In this paper, an active learning framework is proposed to deal with imbalanced data by alternative performing important sampling(ALIS), which consists of selecting important majority-class instances and generating informative minority-class instances. In ALIS, two important sampling strategies affect each other so that the selected majority-class instances provide much clearer information in the next oversampling process, meanwhile the generated minority-class instances provide much more sufficient information for the next undersampling procedure. Extensive experiments have been conducted on real world datasets with a large range of imbalance ratio to verify ALIS. The experimental results demonstrate the superiority of ALIS in terms of several well-known evaluation metrics by comparing with the state-of-the-art methods.

关键词： imbalance classification important sampling active learning oversampling undersampling

来源：评论

学校读者我要写书评

暂无评论

Achieving dynamic privacy measurement and protection based on reinforcement learning for mobile edge crowdsensing of IoT

引用

Digital Communications and networks 2024年第2期10卷 380-388页

作者： Renwan Bi Mingfeng Zhao Zuobin Ying Youliang Tian Jinbo Xiong Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber SecurityFujian Normal UniversityFuzhou350117China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin541004China Faculty of Data Science City University of Macao999078MacaoChina State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China

With the maturity and development of 5G field,Mobile Edge CrowdSensing(MECS),as an intelligent data collection paradigm,provides a broad prospect for various applications in ***,sensing users as data uploaders lack a balance between data benefits and privacy threats,leading to conservative data uploads and low revenue or excessive uploads and privacy *** solve this problem,a Dynamic Privacy Measurement and Protection(DPMP)framework is proposed based on differential privacy and reinforcement ***,a DPM model is designed to quantify the amount of data privacy,and a calculation method for personalized privacy threshold of different users is also ***,a Dynamic Private sensing data Selection(DPS)algorithm is proposed to help sensing users maximize data benefits within their privacy ***,theoretical analysis and ample experiment results show that DPMP framework is effective and efficient to achieve a balance between data benefits and sensing user privacy protection,in particular,the proposed DPMP framework has 63%and 23%higher training efficiency and data benefits,respectively,compared to the Monte Carlo algorithm.

关键词： Mobile edge crowdsensing Dynamic privacy measurement Personalized privacy threshold Privacy protection Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Age of Semantics in Cooperative Communications: To Expedite Simulation Towards Real via Offline Reinforcement Learning

引用

IEEE Transactions on network science and Engineering 2025年

作者： Chen, Xianfu Zhao, Zhifeng Mao, Shiwen Wu, Celimuge Zhang, Honggang Bennis, Mehdi Shenzhen CyberAray Network Technology Co. Ltd. Shenzhen518100 China Zhejiang University Zhejiang Lab Hangzhou310027 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Auburn University Department of Electrical and Computer Engineering AuburnAL36849 United States The University of Electro-Communications Meta-Networking Research Center Chofu-shi Tokyo182-8585 Japan The University of Electro-Communications Graduate School of Informatics and Engineering Chofu-shi Tokyo182-8585 Japan City University of Macau Faculty of Data Science Taipa999078 China University of Oulu Centre for Wireless Communications Oulu90570 Finland

The age of information metric fails to correctly describe the intrinsic semantics of a status update. In an intelligent reflecting surface-aided cooperative relay communication system, we propose the age of semantics (AoS) for measuring the semantics freshness of status updates. Specifically, we focus on status updates from a source node (SN) to the destination, which is formulated as a Markov decision process. The objective of the SN is to maximize the expected satisfaction of AoS and energy consumption under the maximum transmit power constraint. To seek the optimal control policy, we first derive an online deep actor-critic (DAC) learning scheme under the on-policy temporal difference learning framework. However, implementing the online DAC in practice poses key challenge in infinitely repeated interactions between the SN and the system, which can be dangerous particularly during exploration. We then put forward a novel offline DAC scheme, which estimates the optimal control policy from a previously collected dataset without any further interactions with the system. Numerical experiments verify the theoretical results and show that our offline DAC scheme significantly outperforms the online DAC scheme and the most representative baselines in terms of mean utility, demonstrating strong robustness to dataset quality. © 2013 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：