检索结果-内蒙古大学图书馆

DSAFF-Net:A Backbone Network Based on Mask R-CNN for Small Object Detection

Computers, Materials & Continua 2023年第2期74卷 3405-3419页

作者： Jian Peng Yifang Zhao Dengyong Zhang Feng Li Arun Kumar Sangaiah Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computing Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India

Recently,object detection based on convolutional neural networks(CNNs)has developed *** backbone networks for basic feature extraction are an important component of the whole detection ***,we present a new feature extraction strategy in this paper,which name is *** this strategy,we design:1)a sandwich attention feature fusion module(SAFF module).Its purpose is to enhance the semantic information of shallow features and resolution of deep features,which is beneficial to small object detection after feature fusion.2)to add a new stage called D-block to alleviate the disadvantages of decreasing spatial resolution when the pooling layer increases the receptive *** method proposed in the new stage replaces the original method of obtaining the P6 feature map and uses the result as the input of the regional proposal network(RPN).In the experimental phase,we use the new strategy to extract *** experiment takes the public dataset of Microsoft Common Objects in Context(MS COCO)object detection and the dataset of Corona Virus Disease 2019(COVID-19)image classification as the experimental object *** results show that the average recognition accuracy of COVID-19 in the classification dataset is improved to 98.163%,and small object detection in object detection tasks is improved by 4.0%.

关键词： Small object detection classification RPN MS COCO COVID-19

来源：评论

学校读者我要写书评

暂无评论

Finite-Time Anti-Synchronization for Memristive Neural Networks with Time-Varying Delays

引用

IAENG International Journal of Applied Mathematics 2025年第3期55卷 611-617页

作者： Duan, Lian Zhang, Ziyue Li, Ziyang Anhui Province Engineering Laboratory for Big Data Analysis and Early Warning Technology of Coal Mine Safety Department of Mathematics Anhui University of Science and Technology Huainan232001 China Department of Mathematics Anhui University of Science and Technology Huainan232001 China

This paper addresses the finite-time anti-synchronization issue for a type of delayed memristive neural networks. By designing a novel memoryless state-feedback controller, novel criteria on finite-time anti-synchronization of the addressed system are discovered based on drive-response framework, rigorous mathematical analysis techniques and differential inclusions theory. The established theoretical results indicate that the switching between finite-time and fixed-time anti-synchronization depends on the position of the initial functions, which are essentially different from existing switching mechanism. In addition, a simulated example is given to verify the validity of the theoretical findings. © (2025), (International Association of Engineers). All rights reserved.

关键词： State feedback

来源：评论

学校读者我要写书评

暂无评论

MMD GRAPH KERNEL: EFFECTIVE METRIC LEARNING FOR GRAPHS VIA MAXIMUM MEAN DISCREPANCY 12

MMD GRAPH KERNEL: EFFECTIVE METRIC LEARNING FOR GRAPHS VIA M...

引用

12th International Conference on Learning Representations, ICLR 2024

作者： Sun, Yan Fan, Jicong School of Data Science The Chinese University of Hong Kong Shenzhen China School of Computing National University of Singapore Singapore Shenzhen Research Institute of Big Data Shenzhen China

This paper focuses on graph metric learning. First, we present a class of maximum mean discrepancy (MMD) based graph kernels, called MMD-GK. These kernels are computed by applying MMD to the node representations of two graphs with message-passing propagation. Secondly, we provide a class of deep MMD-GKs that are able to learn graph kernels and implicit graph features adaptively in an unsupervised manner. Thirdly, we propose a class of supervised deep MMD-GKs that are able to utilize label information of graphs and hence yield more discriminative metrics. Besides the algorithms, we provide theoretical analysis for the proposed methods. The proposed methods are evaluated in comparison to many baselines such as graph kernels and graph neural networks in the tasks of graph clustering and graph classification. The numerical results demonstrate the effectiveness and superiority of our methods. Our code is available at https://***/yan-sun-x/MMD-Graph-Kernel. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Message passing

来源：评论

学校读者我要写书评

暂无评论

A High-Quality Adaptive Video Reconstruction Optimization Method Based on Compressed Sensing

引用

Computer Modeling in Engineering & sciences 2023年第10期137卷 363-383页

作者： Yanjun Zhang Yongqiang He Jingbo Zhang Yaru Zhao Zhihua Cui Wensheng Zhang School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan030024China Department of Big Data and Intelligent Engineering Shanxi Institute of TechnologyYangquan045000China School of Computer Science Beijing University of TechnologyBeijing100124China The Institute of Automation Chinese Academy of Sciences(CAS)Beijing100049China

The video compression sensing method based onmulti hypothesis has attracted extensive attention in the research of video codec with limited ***,the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging *** resolve this problem,this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction *** includes the optimization of prediction blocks(OPBS),the selection of searchwindows and the use of neighborhood ***,the OPBS consists of two parts:the selection of blocks and the optimization of prediction *** combine the high-quality optimization reconstruction of foreground block with the residual reconstruction of the background block to improve the overall reconstruction effect of the video *** addition,most of the existing methods based on predictive residual reconstruction ignore the impact of search windows and reference frames on ***,Block-level search window(BSW)is constructed to cover the position of the optimal hypothesis block as much as *** maximize the availability of reference frames,Nearby reference frame information(NRFI)is designed to reconstruct the current *** proposed method effectively suppresses the influence of the fluctuation of the prediction block on reconstruction and improves the reconstruction *** results showthat the proposed compressed sensing-based high-quality adaptive video reconstruction optimization method significantly improves the reconstruction performance in both objective and supervisor quality.

关键词： Compressed sensing OPBS block-level search window nearby reference frame information evolutionary algorithm

来源：评论

学校读者我要写书评

暂无评论

PAB-Mamba-YOLO:VSSM assists in YOLO for aggressive behavior detection among weaned piglets

引用

Artificial Intelligence in Agriculture 2025年第1期15卷 52-66页

作者： Xue Xia Ning Zhang Zhibin Guan Xin Chai Shixin Ma Xiujuan Chai Tan Sun Agricultural Information Institute Chinese Academy of Agricultural SciencesBeijing 100081China Key Laboratory of Agricultural Big Data Ministry of Agriculture and Rural AffairsBeijing 100081China School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China

Aggressive behavior among piglets is considered a harmful social *** weaned piglets with intense aggressive behaviors is paramount for pig breeding *** study introduced a novel hybrid model,PAB-Mamba-YOLO,integrating the principles of Mamba and YOLO for efficient visual detection of weaned piglets'aggressive behaviors,including climbing body,nose hitting,biting tail and biting *** the proposed model,a novel CSPVSS module,which integrated the Cross Stage Partial(CSP)structure with the Visual State Space Model(VSSM),has been *** module was adeptly integrated into the Neck part of the network,where it harnessed convolutional capabilities for local feature extraction and leveraged the visual state space to reveal long-distance *** model exhibited sound performance in detecting aggressive behaviors,with an average precision(AP)of 0.976 for climbing body,0.994 for nose hitting,0.977 for biting tail and 0.994 for biting *** mean average precision(mAP)of 0.985 reflected the model's overall effectiveness in detecting all classes of aggressive *** model achieved a detection speed FPS of 69 f/s,with model complexity measured by 7.2 G floating-point operations(GFLOPs)and parameters(Params)of 2.63 *** experiments with existing prevailing models confirmed the superiority of the proposed *** work is expected to contribute a glimmer of fresh ideas and inspiration to the research field of precision breeding and behavioral analysis of animals.

关键词： Aggressive behaviors Weaned piglet Mamba YOLO Hybrid detection model

来源：评论

学校读者我要写书评

暂无评论

MAG molten pool edge detection algorithm based on a fusion of dark channel prior dehazing and image enhancement

引用

Optoelectronics Letters 2024年第10期20卷 607-613页

作者： LIU Weipeng QU Zepeng GONG Xiangrui WANG Yuheng ZHOU Zhengkui School of Electrical Engineering Hebei University of TechnologyTianjin300401China School of Artificial Intelligence and Data Science Hebei University of TechnologyTianjin300401China

Metal active gas(MAG)welding is one of the widely applied welding techniques using argon and carbon dioxide as shielding *** response to the problem of welding halo and drag shadow during the image acquisition process of it,which makes it difficult to accurately extract the contour of the molten pool,this paper proposes a molten pool edge detection method that combines dark channel prior dehazing(DCPD)and improved single scale Retinex image enhancement *** method overcomes the problem of excessive edge noise in the original molten pool image and the difficulty in feature extraction caused by the dark part of the molten pool after DCPD *** comparative experiments and ablation experiments,it has been shown that the algorithm proposed in this paper has significantly improved the enhancement effect and feature extraction effect,extracting accurate and complete molten pool contours.

关键词： welding image algorithm

来源：评论

学校读者我要写书评

暂无评论

BGNN: Behavior-aware graph neural network for heterogeneous session-based recommendation

引用

Frontiers of Computer science 2023年第5期17卷 103-118页

作者： Jinwei LUO Mingkai HE Weike PAN Zhong MING College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen 518060China

Session-based recommendation(SBR)and multibehavior recommendation(MBR)are both important problems and have attracted the attention of many researchers and *** from SBR that solely uses one single type of behavior sequences and MBR that neglects sequential dynamics,heterogeneous SBR(HSBR)that exploits different types of behavioral information(e.g.,examinations like clicks or browses,purchases,adds-to-carts and adds-to-favorites)in sequences is more consistent with real-world recommendation scenarios,but it is rarely *** efforts towards HSBR focus on distinguishing different types of behaviors or exploiting homogeneous behavior transitions in a sequence with the same type of ***,all the existing solutions for HSBR do not exploit the rich heterogeneous behavior transitions in an explicit way and thus may fail to capture the semantic relations between different types of ***,all the existing solutions for HSBR do not model the rich heterogeneous behavior transitions in the form of graphs and thus may fail to capture the semantic relations between different types of *** limitation hinders the development of HSBR and results in unsatisfactory *** a response,we propose a novel behavior-aware graph neural network(BGNN)for *** BGNN adopts a dual-channel learning strategy for differentiated modeling of two different types of behavior sequences in a ***,our BGNN integrates the information of both homogeneous behavior transitions and heterogeneous behavior transitions in a unified *** then conduct extensive empirical studies on three real-world datasets,and find that our BGNN outperforms the best baseline by 21.87%,18.49%,and 37.16%on average correspondingly.A series of further experiments and visualization studies demonstrate the rationality and effectiveness of our *** exploratory study on extending our BGNN to handle more than two types of behaviors show that our BGNN can e

关键词： session-based recommendation graph neural network heterogeneous behaviors

来源：评论

学校读者我要写书评

暂无评论

mVulPreter: A Multi-Granularity Vulnerability Detection System With Interpretations

引用

IEEE Transactions on Dependable and Secure Computing 2022年 1-12页

作者： Zou, Deqing Hu, Yutao Li, Wenke Wu, Yueming Zhao, Haojun Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China School of Computer Science and Engineering Nanyang Technological University Singapore National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Due to the powerful automatic feature extraction, deep learning-based vulnerability detection methods have evolved significantly in recent years. However, almost all current work focuses on detecting vulnerabilities at a single granularity (i.e., slice-level or function-level). In practice, slice-level vulnerability detection is fine-grained but may contain incomplete vulnerability details. Function-level vulnerability detection includes full vulnerability semantics but may contain vulnerability-unrelated statements. Meanwhile, they pay more attention to predicting whether the source code is vulnerable and cannot pinpoint which statements are more likely to be vulnerable. In this paper, we design mVulPreter, a multi-granularity vulnerability detector that can provide interpretations of detection results. Specifically, we propose a novel technique to effectively blend the advantages of function-level and slice-level vulnerability detection models and output the detection results' interpretation only by the model itself. We evaluate mVulPreter on a dataset containing 5,310 vulnerable functions and 7,601 non-vulnerable functions. The experimental results indicate that mVulPreter outperforms existing state-of-the-art vulnerability detection approaches (i.e., Checkmarx, FlawFinder, RATS, TokenCNN, StatementLSTM, SySeVR, and Devign). IEEE

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Evaluating quality of motion for unsupervised video object segmentation

引用

Optoelectronics Letters 2024年第6期20卷 379-384页

作者： CHENG Guanjun SONG Huihui Jiangsu Key Laboratory of Big Data Analysis Technology Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologyNanjing University of Information Science&TechnologyNanjing 210044China12

Current mainstream unsupervised video object segmentation(UVOS) approaches typically incorporate optical flow as motion information to locate the primary objects in coherent video frames. However, they fuse appearance and motion information without evaluating the quality of the optical flow. When poor-quality optical flow is used for the interaction with the appearance information, it introduces significant noise and leads to a decline in overall performance. To alleviate this issue, we first employ a quality evaluation module(QEM) to evaluate the optical flow. Then, we select high-quality optical flow as motion cues to fuse with the appearance information, which can prevent poor-quality optical flow from diverting the network's attention. Moreover, we design an appearance-guided fusion module(AGFM) to better integrate appearance and motion information. Extensive experiments on several widely utilized datasets, including DAVIS-16, FBMS-59, and You Tube-Objects, demonstrate that the proposed method outperforms existing methods.

关键词： Evaluating quality of motion for unsupervised video object segmentation

来源：评论

学校读者我要写书评

暂无评论

A Novel Four-State Switchable Dual-Band Bandpass Filter with High OFF-State Suppression Based on Multi-Mode Resonators

引用

Progress In Electromagnetics Research C 2024年 144卷 189-198页

作者： Yang, Bingjie Wang, Zhongbao Liu, Hongmei Gao, Mingming Fang, Shaojun School of Information Science and Technology Dalian Maritime University Liaoning Dalian116026 China Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications Liaoning Technical University Liaoning Huludao125105 China

A novel switchable dual-band bandpass filter (BPF) is proposed, where each passband can be independently controlled. The filter is composed of a tri-mode resonator, a dual-mode resonator, and feed lines coupling with the resonators. By controlling the PIN diodes loaded on the open end of the resonators, four operating states (i.e., dual bands, lower passband, upper passband, and all-stop band) are realized. A switchable dual-band BPF prototype is designed, fabricated, and measured with the center frequencies of 1.575 and 2.45 GHz having the bandwidths of 300 and 220 MHz, respectively. The prototype occupies an area of 0.128λ2g, where λg is the guided wavelength at the center frequency of the lower band (1.575 GHz). The measurement results indicate that the proposed switchable dual-band BPF has low insertion loss and high OFF-state suppression. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Bandpass filters

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：