检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Sun, Geng Wang, Yixian Sun, Zemin Wu, Qingqing Kang, Jiawen Niyato, Dusit Leung, Victor C.M. College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China School of Automation Guangdong University of Technology Guangzhou510006 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Recent developments in unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) have provided users with flexible and resilient computing services. However, meeting the computing-intensive and latency-sensitive demands of users poses a significant challenge due to the limited resources of UAVs. To address this challenge, we present a multi-objective optimization approach for multi-UAV-assisted MEC systems. First, we formulate a multi-objective optimization problem aiming at minimizing the total task completion delay, reducing the total UAV energy consumption, and maximizing the total amount of offloaded tasks by jointly optimizing task offloading, computation resource allocation, and UAV trajectory control. Since the problem is a mixed-integer non-linear programming (MINLP) and NP-hard problem which is challenging, we propose a joint task offloading, computation resource allocation, and UAV trajectory control (JTORATC) approach to solve the problem. However, since the decision variables of task offloading, computation resource allocation, and UAV trajectory control are coupled with each other, the original problem is split into three sub-problems, i.e., task offloading, computation resource allocation, and UAV trajectory control, which are solved individually to obtain the corresponding decisions. Moreover, the sub-problem of task offloading is solved by using distributed splitting and threshold rounding methods, the sub-problem of computation resource allocation is solved by adopting the Karush-Kuhn-Tucker (KKT) method, and the sub-problem of UAV trajectory control is solved by employing the successive convex approximation (SCA) method. Simulation results show that the proposed JTORATC has superior performance compared to the other benchmark methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Research on Coordinated Development of Ecological Resources, Environment and Economy and Society in Sanjiang Region

引用

IOP Conference Series: Earth and Environmental science 2020年第1期508卷

作者： Tingting Xue Yaosheng Zhang Xue Wang Chenchen Zhao Lan Li School of Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

An excellent environmental resource environment is a necessary condition for coordinated economic and social development in the Sanjiang region. This article uses four methods of literature review, qualitative analysis and quantitative analysis, static analysis and dynamic analysis, and a combination of theory and empirical research to comprehensively evaluate the degree of coordinated development and coordinated development of eco-resources, environment, economy and society in the Sanjiang region. Analyze the coordinated development of ecological resources, environment, and economy in the Sanjiang region and its spatiotemporal evolution, and propose specific suggestions and countermeasures. The study found that economic development and environmental protection are the two main issues facing social development in the Sanjiang Plain. On the one hand, we must rely on science and technology to vigorously develop the economy, promote the upgrading of the industrial structure, and then promote the development of regional society. The protection of the environment and avoiding environmental degradation direct constraints the development of human culture.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Region-wise generative adversarial image inpainting for large missing areas

arXiv

引用

arXiv 2019年

作者： Ma, Yuqing Liu, Xianglong Bai, Shihao Wang, Lei Liu, Aishan Tao, Dacheng Hancock, Edwin State Key Lab of Software Development Environment Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine UBTECH Sydney Artificial Intelligence Centre School of Information Technologies Faculty of Engineering and Information Technologies University of Sydney DarlingtonNSW2008 Australia Department of Computer Science University of York York United Kingdom

Recently deep neutral networks have achieved promising performance for filling large missing regions in image inpainting tasks. They usually adopted the standard convolutional architecture over the corrupted image, leading to meaningless contents, such as color discrepancy, blur and artifacts. Moreover, most inpainting approaches cannot well handle the large contiguous missing area cases. To address these problems, we propose a generic inpainting framework capable of handling with incomplete images on both contiguous and discontiguous large missing areas, in an adversarial manner. From which, region-wise convolution is deployed in both generator and discriminator to separately handle with the different regions, namely existing regions and missing ones. Moreover, a correlation loss is introduced to capture the non-local correlations between different patches, and thus guides the generator to obtain more information during inference. With the help of our proposed framework, we can restore semantically reasonable and visually realistic images. Extensive experiments on three widely-used datasets for image inpainting tasks have been conducted, and both qualitative and quantitative experimental results demonstrate that the proposed model significantly outperforms the state-of-the-art approaches, both on the large contiguous and discontiguous missing areas. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Deep Common Feature Mining for Efficient Video Semantic Segmentation

arXiv

引用

arXiv 2024年

作者： Zheng, Yaoyan Yang, Hongyu Huang, Di State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Shanghai Artificial Intelligence Laboratory Shanghai201112 China Zhejiang Industrial Big Data and Robot Intelligent System Key Laboratory Hangzhou Innovation Institute Beihang University Hangzhou310051 China

Recent advancements in video semantic segmentation have made substantial progress by exploiting temporal correlations. Nevertheless, persistent challenges, including redundant computation and the reliability of the feature propagation process, underscore the need for further innovation. In response, we present Deep Common Feature Mining (DCFM), a novel approach strategically designed to address these challenges by leveraging the concept of feature sharing. DCFM explicitly decomposes features into two complementary components. The common representation extracted from a key-frame furnishes essential high-level information to neighboring non-key frames, allowing for direct re-utilization without feature propagation. Simultaneously, the independent feature, derived from each video frame, captures rapidly changing information, providing frame-specific clues crucial for segmentation. To achieve such decomposition, we employ a symmetric training strategy tailored for sparsely annotated data, empowering the backbone to learn a robust high-level representation enriched with common information. Additionally, we incorporate a self-supervised loss function to reinforce intra-class feature similarity and enhance temporal consistency. Experimental evaluations on the VSPW and Cityscapes datasets demonstrate the effectiveness of our method, showing a superior balance between accuracy and efficiency. The implementation is available at https://***/BUAAHugeGun/DCFM. © 2024, CC BY-NC-SA.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Transport Waste Separation and Recovery Trajectory Judged Based on Dijkstra's Algorithm

引用

IOP Conference Series: Earth and Environmental science 2020年第1期526卷

作者： Yanbin Sun Penglin Shen Huimin Jiang Yuehua Zhang Jinqiu Guan Lan Li School of Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

Urban waste classification and recycling is an important research node in people's livelihood, which is related to the corresponding relationship between efficiency and quality. The optimization of the recycling transportation path means that the cost is less. In the process of garbage transportation classification and recycling, optimizing and merging the routes of garbage transportation based on Dijkstra's algorithm can optimize the shared transportation resources, to achieve the result of saving operating costs. The immediate transportation recycling event is planned as the path planning optimization. Multi-source multi-object and multi-path planning problems, and rehearse the optimization model of the total length of the transport path set without repeated paths. When the scale of the transportation and recovery network grows to a set value, it is difficult to achieve a theoretical solution by accurately calculating the optimal value of the model through an optimization algorithm. An optimal path set selection algorithm based on a random walk is feasible. The effectiveness and operability of the method are verified by small experiments and simulation experiments. The path is the shortest, and compared with the summation algorithm, it not only has high accuracy, but also has high execution efficiency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Main Meteorological Factors Inside and Outside the Forest of Xianweng Mountain National Forest Park

引用

IOP Conference Series: Earth and Environmental science 2020年第1期508卷

作者： Guoli Ren Xuewen Yang Xue Wang Yaosheng Zhang Shengju Li Lan Li School of Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

Investigations of meteorological conditions can reveal the dynamics of microclimates in specific forests. Meteorological factors are necessary factors for quantitative observation and research of forest ecosystems. A systematic analysis of the forest boundary and the main meteorological factors outside the forest in Xianweng Mountain National Forest Park can accurately reveal the interaction between the forest and meteorological factors in Xianweng Mountain National Forest Park. Based on the meteorological observation data of the forest of Xianweng Mountain National Forest Park for three consecutive years, and using experimental methods to locate meteorological factors inside and outside the forest, compare meteorological factors such as atmospheric temperature, relative humidity, precipitation and wind speed, and wind direction, and analyze their different characteristics. The results show that the main reason for the difference in temperature and humidity inside and outside the forest is that the canopy absorbs solar radiation and emits long-wave radiation from the ground. The dense canopy also impedes air exchange inside and outside the forest, reducing wind speeds in the woods. Meteorological factors play an important role in guiding the distribution of forests, and have an important impact on the growth of trees in the forest, the development of trees, and the accumulation of tree biomass. A systematic comparative analysis of the main meteorological factors inside and outside the forest of Xianweng Mountain National Forest Park revealed the interaction between the forest and meteorological factors of Xianweng Mountain National Forest Park. According to the meteorological observation data of Xianweng Mountain National Forest Park, in order to make reasonable use of meteorological resources in the future, to develop forests, to protect the balance of natural ecosystems and their healthy development are of great significance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Study on Eco-health Evaluation of Ledum-Larixgmelinii Forest in Cold Temperate Zone

引用

IOP Conference Series: Earth and Environmental science 2020年第1期526卷

作者： Ye Gu Penglin Shen Guoli Ren Wu Zhang Yuehua Zhang Jinqiu Guan Lan Li School of Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

Field surveys set standard measurement indicators, use principal component analysis to screen indicators, determine weights, construct evaluation models, and use cluster analysis to classify Durian larch forest health grades. Three types of Ledum-Larixgmelinii forest in the clearcut forest were studied for health evaluation. The results of the study show that: forest stand productivity, soil nutrients, organizational structure, resistance, and resilience have identified 19 indicators that are more important for the health of Duxiang-Xing'an larch forest. A forest health assessment index system of Ledum-Larixgmelinii forest was established. The principal component analysis method was used to select comprehensive indexes such as comprehensiveness, resilience, plant diseases, and insect pests, plant species diversity, fire disturbance degree, structural rationality, soil nutrients and natural disturbance, as the evaluation indicators of Ledum-Larixgmelinii larch forest. Although the overall health status of the Ledum-Larixgmelinii forest is generally good, there are still areas of forest with health problems. Through analysis, the primary forest has the highest health index and the best health status. It can be seen that the forest grown in the original state has a stable structure, high vitality, strong resistance, and strong sustainability. The health level of the declining forest is second only to that of the primary forest. In clearing forests, there are two kinds of clearing forests in the study area. Among them, 2/3 of the forest are poor, and 1/3 of the forest are in the middle, but the health of the clear cutting forest is the lowest overall.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Online Attentive Kernel-Based Temporal Difference Learning

arXiv

引用

arXiv 2022年

作者： Yang, Guang Chen, Xingguo Yang, Shangdong Wang, Huihui Dong, Shaokang Gao, Yang The the Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications National Engineering Laboratory for Agri-Product Quality Traceability Beijing Technology and Business University China The State Key Laboratory for Novel Software Technology Nanjing University China The PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology China

With rising uncertainty in the real world, online Reinforcement Learning (RL) has been receiving increasing attention due to its fast learning capability and improving data efficiency. However, online RL often suffers from complex Value Function Approximation (VFA) and catastrophic interference, creating difficulty for the deep neural network to be applied to an online RL algorithm in a fully online setting. Therefore, a simpler and more adaptive approach is introduced to evaluate value function with the kernel-based model. Sparse representations are superior at handling interference, indicating that competitive sparse representations should be learnable, non-prior, non-truncated and explicit when compared with current sparse representation methods. Moreover, in learning sparse representations, attention mechanisms are utilized to represent the degree of sparsification, and a smooth attentive function is introduced into the kernel-based VFA. In this paper, we propose an Online Attentive Kernel-Based Temporal Difference (OAKTD) algorithm using two-timescale optimization and provide convergence analysis of our proposed algorithm. Experimental evaluations showed that OAKTD outperformed several Online Kernel-based Temporal Difference (OKTD) learning algorithms in addition to the Temporal Difference (TD) learning algorithm with Tile Coding on public Mountain Car, Acrobot, CartPole and Puddle World tasks. Copyright © 2022, The Authors. All rights reserved.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Dual Representation Learning for One-Step Clustering of Multi-View data

arXiv

引用

arXiv 2022年

作者： Zhang, Wei Deng, Zhaohong Choi, Kup-Sze Wang, Jun Wang, Shitong The School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Key Laboratory of Media Design and Software Technology Wuxi214122 China The School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China ZJLab Shanghai200433 China The Centre for Smart Health The Hong Kong Polytechnic University Hong Kong The Key laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University Shanghai200444 China

Multi-view data are commonly encountered in data mining applications. Effective extraction of information from multi-view data requires specific design of clustering methods to cater for data with multiple views, which is non-trivial and challenging. In this paper, we propose a novel one-step multi-view clustering method by exploiting the dual representation of both the common and specific information of different views. The motivation originates from the rationale that multi-view data contain not only the consistent knowledge between views but also the unique knowledge of each view. Meanwhile, to make the representation learning more specific to the clustering task, a one-step learning framework is proposed to integrate representation learning and clustering partition as a whole. With this framework, the representation learning and clustering partition mutually benefit each other, which effectively improves the clustering performance. Results from extensive experiments conducted on benchmark multi-view datasets clearly demonstrate the superiority of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

Multi-stage image denoising with the wavelet transform

arXiv

引用

arXiv 2022年

作者： Tian, Chunwei Zheng, Menghua Zuo, Wangmeng Zhang, Bob Zhang, Yanning Zhang, David School of Software Northwestern Polytechnical University Shaanxi Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Xi’an710129 China School of Computer Science and Technology Harbin Institute of Technology Heilongjiang Harbin150001 China Peng Cheng Laboratory Guangdong Shenzhen518055 China Department of Computer and Information Science University of Macau 999078 China School of Computer Science Northwestern Polytechnical University Shaanxi Xi’an710129 China Guangdong Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

Deep convolutional neural networks (CNNs) are used for image denoising via automatically mining accurate structure information. However, most of existing CNNs depend on enlarging depth of designed networks to obtain better denoising performance, which may cause training difficulty. In this paper, we propose a multi-stage image denoising CNN with the wavelet transform (MWDCNN) via three stages, i.e., a dynamic convolutional block (DCB), two cascaded wavelet transform and enhancement blocks (WEBs) and a residual block (RB). DCB uses a dynamic convolution to dynamically adjust parameters of several convolutions for making a tradeoff between denoising performance and computational costs. WEB uses a combination of signal processing technique (i.e., wavelet transformation) and discriminative learning to suppress noise for recovering more detailed information in image denoising. To further remove redundant features, RB is used to refine obtained features for improving denoising effects and reconstruct clean images via improved residual dense architectures. Experimental results show that the proposed MWDCNN outperforms some popular denoising methods in terms of quantitative and qualitative analysis. Codes are available at https://***/hellloxiaotian/MWDCNN. © 2022, CC BY-NC-ND.

关键词： Wavelet transforms

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：