检索结果-内蒙古大学图书馆

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Wang, Yingqian Wang, Longguang Liang, Zhengyu Yang, Jungang Timofte, Radu Guo, Yulan Jin, Kai Wei, Zeqiang Yang, Angulia Guo, Sha Gao, Mingzhi Zhou, Xiuzhuang Van Duong, Vinh Huu, Thuc Nguyen Yim, Jonghoon Jeon, Byeungwoo Liu, Yutong Cheng, Zhen Xiao, Zeyu Xu, Ruikang Xiong, Zhiwei Liu, Gaosheng Jin, Manchang Yue, Huanjing Yang, Jingyu Gao, Chen Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Xia, Wang Wang, Yan Xia, Peiqi Wang, Shunzhou Lu, Yao Cong, Ruixuan Sheng, Hao Yang, Da Chen, Rongshan Wang, Sizhe Cui, Zhenglong Chen, Yilei Lu, Yongjie Cai, Dongjun An, Ping Salem, Ahmed Ibrahem, Hatem Yagoub, Bilel Kang, Hyun-Soo Zeng, Zekai Wu, Heng National University of Defense Technology China Aviation University of Air Force China University of Würzburg Germany Eth Zürich Switzerland Sun Yat-sen University The Shenzhen Campus of Sun Yat-sen University China Bigo Technology Pte. Ltd. Singapore Smart Medical Innovation Lab Beijing University of Posts and Telecommunications China Global Explorer Ltd. Suzhou China National Engineering Research Center of Visual Technology School of Computer Science Peking University China School of Artificial Intelligence Beijing University of Posts and Telecommunications China Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of University of Science and Technology of China China School of Electrical and Information Engineering Tianjin University China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada Beijing Institute of Technology China Shenzhen MSU-BIT University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China School of Communication and Information Engineering Shanghai University China School of Information and Communication Engineering Chungbuk National University Korea Republic of Guangdong University of Technology China

ISBN: (纸本)9798350302493

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information from plenty of views with varying disparities. In total, 148 participants have registered the challenge, and 11 teams have successfully submitted results with PSNR scores higher than the baseline method LF-InterNet [1]. These newly developed methods have set new state-of-the-art in LF image SR, e.g., the winning method achieves around 1 dB PSNR improvement over the existing state-of-the-art method DistgSSR [2]. We report the solutions proposed by the participants, and summarize their common trends and useful tricks. We hope this challenge can stimulate future research and inspire new ideas in LF image SR. © 2023 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

A Matching Based Escape Routing Algorithm With Variable Design Rules and Multiple Constraints

引用

IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Chen, Chuandong Lin, Disi Liu, Qinghai He, Huan Lin, Zhifeng Liu, Genggeng Chen, Jianli Chang, Yao-Wen Fuzhou University Department of Microelectronics Fuzhou350108 China Fuzhou University Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Center for Applied Mathematics of Fujian Province Center for Discrete Mathematics Fuzhou350108 China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou310000 China Fuzhou University Center for Discrete Mathematics and Theoretical Computer Science Fuzhou350108 China Fuzhou University College of Computer and Data Science Fuzhou350108 China Fudan University School of Microelectronics Shanghai200433 China National Taiwan University Department of Electrical Engineering Graduate Institute of Electronics Engineering Taipei106 Taiwan

Escape routing is a critical problem in PCB routing, and its quality dramatically affects the cost of the PCB design. Unlike the traditional escape routing that works mainly for the BGA with unique line width and space, this paper presents a high-performance escape routing algorithm to handle problems with variable design rules and multiple constraints. We first propose a novel obstacle-avoiding method to project pins to the boundary and construct a channel projection graph combined with a channel merging technique to handle complex irregular packages. We then construct a bi-projection graph and propose a matching-based hierarchical sequencing algorithm to consider manual constraints. We perform global routing for each pin/differential pair by congestion-avoiding path initializing and rip-up and reroute path optimizing. Finally, a length-aware detail routing algorithm is developed to optimize the line length while ensuring the differential pair constraints. The experimental results on industrial PCB instances show that our algorithm can achieve 100% routability without violating the design rules and constraints, while two state-of-the-art PCB routers, FreeRouting and Allegro, cannot complete escape routing. © 1982-2012 IEEE.

关键词： Printed circuit design

来源：评论

学校读者我要写书评

暂无评论

A Multiscale Orchestrated Computational Framework to Reveal Emergent Phenomena in Neuroblastoma

SSRN

引用

SSRN 2023年

作者： Carlos, Borau Wertheim, K.Y. Hervas-Raluy, S. Sainz-DeMena, D. Walker, D. Chisholm, R. Richmond, P. Varella, V. Viceconti, M. Montero, A. Gregori-Puigjané, E. Mestres, J. Kasztelnik, M. García-Aznar, J.M. Mechanical Engineering Dept University of Zaragoza Zaragoza Spain Department of Computer Science Insigneo Institute for In Silico Medicine University of Sheffield Sheffield United Kingdom Department of Industrial Engineering Alma Mater Studiorum University of Bologna Italy Medical Technology Lab IRCCS Istituto Ortopedico Rizzoli Bologna Italy Baldiri Reixac 4 Barcelona Spain ACC Cyfronet AGH University of Science and Technology Kraków Poland Centre of Excellence for Data Science Artificial Intelligence and Modelling and School of Computer Science University of Hull Kingston upon Hull United Kingdom

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumors, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. This model, integrated into an online platform, will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This work outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development. © 2023, The Authors. All rights reserved.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

A Survey on Network Management for xANET: Evolution, Challenges, Future Directions

引用

IEEE Communications Surveys and Tutorials 2025年

作者： Li, Tong Yang, Chungang Wang, Yao Cai, Lin Anpalagan, Alagan Han, Zhu Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China National Key Laboratory of Multi-domain Data Collaborative Processing and Control Xi'an710068 China Hangzhou Institute of Technology of Xidian University Hangzhou311231 China University of Victoria Department of Electrical and Computer Engineering VictoriaBCV8P 5C2 Canada Ryerson University Department of Electrical and Computer Engineering TorontoONM5B 2K3 Canada University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446701 Korea Republic of

The x ad hoc network (xANET) termed as a family of ad hoc networks, including mobile ad hoc network (MANET), vehicular ad hoc network (VANET), flying ad hoc network (FANET) and satellite ad hoc network (SANET), has found a wide range of applications in providing ubiquitous wireless services. Despite its broad utility, the dynamic nature and lack of a centralized controller pose significant challenges to effective and flexible network management for xANET. Conventional network management protocols face challenges such as scalability, security vulnerabilities, configuration complexity, robustness, and performance resilience. Recent efforts have presented different approaches, focusing on policy-based network management (PBNM) and intent-driven network management (IDNM). However, there is no comprehensive survey to clarify their concepts and classifications. This paper presents a survey of the network management evolution for xANET, covering configuration-based, policy-based and the latest intent-driven approaches. We first introduce the characteristics and applications of xANET. Meanwhile, we investigate the network management concepts and challenges. Moreover, we survey the evolution of management protocols for xANET, including simple network management protocol (SNMP), PBNM, and IDNM. Then, we follow the detailed network management of xANET from configuration-based to policy-based and intent-driven approaches. Through comparative analysis, it is found that IDNM employs a more intelligent management protocol, demonstrating higher efficiency and flexibility in handling complex tasks and dynamic network management. This makes it better suited to addressing the challenges of xANET management. Finally, we summarize the remaining challenges and possible future research directions. © 2025 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

A Novel Dynamic Watermarking for Secure data Protection from Cyber Theft Based on Artificial Intelligence Supervision

A Novel Dynamic Watermarking for Secure Data Protection from...

引用

International Conference on science Technology engineering and Management (ICONSTEM)

作者： Ravikiran Madala R. Monica Sulakshana Sagar Malwade Selvakumaran. S Shilpa Jivan Budhavale N. Sathyabalaji Information Technology University of Cumberlands Durham North Carolina United States Department of Electronics and Communication Engineering Nandha Engineering College Erode TamilNadu India Department of Computer Engineering Dr.Vishwanath Karad School of Polytechnic and Skill Development Pune Maharashtra India Department of Artificial Intelligence and Data Science Rajalakshmi Institute of Technology Chennai TamilNadu India Department of Computer Engineering Dr. Vishwanath Karad School of Polytechnic and Skill Development Pune Maharashtra India Department of Computer Science and Engineering JKK Munirajah College of Technology Erode TamilNadu India

One of the centre innovations of the Fourth Modern Insurgency (otherwise called Industry 4.0) is artificial intelligence (computer based intelligence), which can be utilized to shield Web associated gadgets from dangers, assaults, harm, and undesirable access. The current range of cyber security issues can be deftly handled by utilising well-known simulated intelligence techniques such as AI and profound learning procedures, the possibility of normal language handling, information portrayal and thinking, as well as the possibility of information or rule-based master frameworks displaying. In view of these man-made intelligence strategies, we give an exhaustive examination of "Simulated intelligence driven cyber security" in this article, which may be helpful for clever cyber security government agencies and the board. The cyber security registration method can be made more computerised and intelligent than the standard security frameworks by the security intelligence exhibiting in light of such simulated intelligence ***, we present various choices for future examination that fall inside the domain of our examination. At last, this paper's primary objective is to give direction and references to industry specialists in the field of cyber security, especially from a canny registering or simulated intelligence based specialized viewpoint.

关键词：

来源：评论

学校读者我要写书评

暂无评论

LatentColorization: Latent Diffusion-Based Speaker Video Colorization

arXiv

引用

arXiv 2024年

作者： Ward, Rory Bigioi, Dan Basak, Shubhajit Breslin, John G. Corcoran, Peter SFI Centre for Research Training in Artificial Intelligence Data Science Institute University of Galway University Road H91 TK33 Ireland School of Computer Science University of Galway University Road GalwayH91 TK33 Ireland School of Engineering University of Galway University Road GalwayH91 TK33 Ireland

While current research predominantly focuses on image-based colorization, the domain of video-based colorization remains relatively unexplored. Most existing video colorization techniques operate on a frame-by-frame basis, often overlooking the critical aspect of temporal coherence between successive frames. This approach can result in inconsistencies across frames, leading to undesirable effects like flickering or abrupt color transitions between frames. To address these challenges, we harness the generative capabilities of a fine-tuned latent diffusion model designed specifically for video colorization, introducing a novel solution for achieving temporal consistency in video colorization, as well as demonstrating strong improvements on established image quality metrics compared to other existing methods. Furthermore, we perform a subjective study, where users preferred our approach to the existing state of the art. Our dataset encompasses a combination of conventional datasets and videos from television/movies. In short, by leveraging the power of a fine-tuned latent diffusion-based colorization system with a temporal consistency mechanism, we can improve the performance of automatic video colorization by addressing the challenges of temporal inconsistency. A short demonstration of our results can be seen in some example videos available at https://***/vDbzsZdFuxM. © 2024, CC BY.

关键词： Diffusion

来源：评论

学校读者我要写书评

暂无评论

Large Scale Model Enabled Semantic Communications Based on Robust Knowledge Distillation

Large Scale Model Enabled Semantic Communications Based on R...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Kuiyuan Ding Fangfang Liu Yang Yang Mingzhe Chen Caili Guo Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering and the Institute for Data Science and Computing University of Miami Coral Gables FL USA Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Large scale artificial intelligence (AI) models possess excellent capabilities in semantic representation and understanding, making them particularly well-suited for semantic encoding and decoding. However, the substantial scale of these AI models imposes unacceptable computational resources and communication delays. To address this issue, we propose a semantic communication scheme based on robust knowledge distillation (RKD-SC) for large scale model enabled semantic communications. In the considered system, a transmitter extracts the features of the source image for robust transmission and accurate image classification at the receiver. To effectively utilize the superior capability of large scale model while make the cost affordable, we first transfer knowledge from a large scale model to a smaller scale model to serve as the semantic encoder. Then, to enhance the robustness of the system against channel noise, we propose a channel-aware autoencoder (CAA) based on the Transformer architecture. Experimental results show that the encoder of proposed RKD-SC system can achieve over 93.3% of the performance of a large scale model while compressing 96.67% number of parameters. Code: https://***/echojayne/RKD-SC.

关键词： Transmitters Computational modeling Noise Autoencoders Receivers Semantic communication Transformers Feature extraction Robustness Decoding

来源：评论

学校读者我要写书评

暂无评论

Modeling and Performance Analysis for Movable Antenna Enabled Wireless Communications

arXiv

引用

arXiv 2022年

作者： Zhu, Lipeng Ma, Wenyan Zhang, Rui The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China

In this paper, we propose a novel antenna architecture called movable antenna (MA) to improve the performance of wireless communication systems. Different from conventional fixed-position antennas (FPAs) that undergo random wireless channel variation, the MAs with the capability of flexible movement can be deployed at positions with more favorable channel conditions to achieve higher spatial diversity gains. To characterize the general multi-path channel in a given region or field where the MAs are deployed, a field-response model is developed by leveraging the amplitude, phase, and angle of arrival/angle of departure (AoA/AoD) information on each of the multiple channel paths under the far-field condition. Based on this model, we then analyze the maximum channel gain achieved by a single receive MA as compared to its FPA counterpart in both deterministic and stochastic channels. First, in the deterministic channel case, we show the periodic behavior of the multi-path channel gain in a given spatial field, which can be exploited for analyzing the maximum channel gain of the MA. Next, in the case of stochastic channels, the expected value of an upper bound on the maximum channel gain of the MA in an infinitely large receive region is derived for different numbers of channel paths. The approximate cumulative distribution function (CDF) for the maximum channel gain is also obtained in closed form, which is useful to evaluate the outage probability of the MA system. Moreover, our results reveal that higher performance gains by the MA over the FPA can be acquired when the number of channel paths increases due to more pronounced small-scale fading effects in the spatial domain. Numerical examples are presented which validate our analytical results and demonstrate that the MA system can reap considerable performance gains over the conventional FPA systems with/without antenna selection (AS), and even achieve comparable performance to the single-input multiple-output (SIMO)

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Local-Global Transformer for Temporal Sentence Grounding

arXiv

引用

arXiv 2022年

作者： Fang, Xiang Liu, Daizong Zhou, Pan Xu, Zichuan Li, Ruixuan Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Wangxuan Institute of Computer fTechnology Peking University No. 128 Zhongguancun North Street Beijing100080 China School of software Dalian University of Technology Dalian116024 China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

This paper studies the multimedia problem of temporal sentence grounding (TSG), which aims to accurately determine the specific video segment in an untrimmed video according to a given sentence query. Traditional TSG methods mainly follow the top-down or bottom-up framework and are not end-to-end. They severely rely on time-consuming post-processing to refine the grounding results. Recently, some transformer-based approaches are proposed to efficiently and effectively model the fine-grained semantic alignment between video and query. Although these methods achieve significant performance to some extent, they equally take frames of the video and words of the query as transformer input for correlating, failing to capture their different levels of granularity with distinct semantics. To address this issue, in this paper, we propose a novel Hierarchical Local-Global Transformer (HLGT) to leverage this hierarchy information and model the interactions between different levels of granularity and different modalities for learning more fine-grained multi-modal representations. Specifically, we first split the video and query into individual clips and phrases to learn their local context (adjacent dependency) and global correlation (long-range dependency) via a temporal transformer. Then, a global-local transformer is introduced to learn the interactions between the local-level and global-level semantics for better multimodal reasoning. Besides, we develop a new cross-modal cycle-consistency loss to enforce interaction between two modalities and encourage the semantic alignment between them. Finally, we design a brand-new cross-modal parallel transformer decoder to integrate the encoded visual and textual features for final grounding. Extensive experiments on three challenging datasets (ActivityNet Captions, Charades-STA and TACoS) show that our proposed HLGT achieves a new state-of-the-art performance, demonstrating its effectiveness and computational efficiency. Copyright ©

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Label

arXiv

引用

arXiv 2022年

作者： Hu, Shengshan Zhou, Ziqi Zhang, Yechao Zhang, Leo Yu Zheng, Yifeng He, Yuanyuan Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China School of Information Technology Deakin University VIC3216 Australia School of Computer Science and Technology Harbin Institute of Technology Shenzhen China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security HUST Wuhan430074 China Cluster and Grid Computing Lab HUST Wuhan430074 China

Due to its powerful feature learning capability and high efficiency, deep hashing has achieved great success in large-scale image retrieval. Meanwhile, extensive works have demonstrated that deep neural networks (DNNs) are susceptible to adversarial examples, and exploring adversarial attack against deep hashing has attracted many research efforts. Nevertheless, backdoor attack, another famous threat to DNNs, has not been studied for deep hashing yet. Although various backdoor attacks have been proposed in the field of image classification, existing approaches failed to realize a truly imperceptive backdoor attack that enjoys invisible triggers and clean label setting simultaneously, and they also cannot meet the intrinsic demand of image retrieval backdoor. In this paper, we propose BadHash, the first generative-based imperceptible backdoor attack against deep hashing, which can effectively generate invisible and input-specific poisoned images with clean label. Specifically, we first propose a new conditional generative adversarial network (cGAN) pipeline to effectively generate poisoned samples. For any given benign image, it seeks to generate a natural-looking poisoned counterpart with a unique invisible trigger. In order to improve the attack effectiveness, we introduce a label-based contrastive learning network LabCLN to exploit the semantic characteristics of different labels, which are subsequently used for confusing and misleading the target model to learn the embedded trigger. We finally explore the mechanism of backdoor attacks on image retrieval in the hash space. Extensive experiments on multiple benchmark datasets verify that BadHash can generate imperceptible poisoned samples with strong attack ability and transferability over state-of-the-art deep hashing schemes. © 2022, CC BY.

关键词： Deep neural networks

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：