检索结果-内蒙古大学图书馆

作者： Xie, Zhonghui Kong, Wa Zhou, Xinyu Zhang, Wence Zhong, Yujie Xia, Jing School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Jiangsu University Zhenjiang China Department of Electronic Information Engineering Hong Kong Polytechnic University Hong Kong

In the manufacturing process of power amplifier (PA), various defects on the circuit surface will seriously affect the circuit performance and its operation. To solve the above problems, this article proposes a circuit defect detection method based on improved patch-based support vector data description algorithm (Patch SVDD), which uses contrastive learning to enhance the feature extraction ability of neural network. An image calibration algorithm is used for calibration preprocessing to enhance the robustness of the model. The Euclidean distance between a query image patch and its nearest normal patch is defined to be an anomaly score. For verification, three defects in the PA circuit, including components missing, solder contamination and component orientation dislocation, were detected. The experimental results show that, compared with conventional method, the area under receiver operating characteristic (AUROC) of the improved anomaly detection model increased from 90.1% to 95.1%, which improves the detection accuracy effectively. © 2023 John Wiley & Sons Ltd.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Fast Prediction Method for PIM Distribution on Waveguide Temperature Compensation Structure Using DC Non-Linearity Diagnosis

Fast Prediction Method for PIM Distribution on Waveguide Tem...

引用

2023 IEEE MTT-S International Wireless Symposium, IWS 2023

作者： Che, Chang Chen, Xiong Yu, Ming The Chinese University of Hong Kong Electronic Engineering Department Hong Kong Southern University of Science and Technology Shenzhen Key Laboratory of em Information Shenzhen518055 China

ISBN: (纸本)9798350336535

This paper proposes a fast prediction method for PIM distribution in the waveguide resonator with temperature compensation (TC) structure. When faced with temperature changes, the waveguide filters expand or contract, affecting the size-dependent resonant frequency. Therefore, filters with high selectivity necessitate temperature compensation structures to ensure thermal stability under stringent circumstances, especially in space applications. Structural connections and contacts always exist in the TC structures, serving as typical sources of passive intermodulation (PIM). When compensation appears, the mechanical deformation accompanying thermal stress will complicate the PIM analysis. DC non-linearity diagnosis is applied in this proposed method, which can fast predict the PIM distribution in TC structures without the PIM test. This prediction method can significantly cut off the testing cost and attain high efficiency in PIM analysis. © 2023 IEEE.

关键词： Waveguide filters

来源：评论

学校读者我要写书评

暂无评论

Apple leaf disease recognition in natural scenes based on re-parameterized SSD algorithm

Apple leaf disease recognition in natural scenes based on re...

引用

2022 International Conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2022

作者： Luo, Wenjie Cai, Linqing Yang, Yanhua School of Information Science & Engineering Yunnan University Yunnan Province 650500 China University Key Laboratory of Internet of Things Technology and Application Yunnan Province 650500 China

ISBN: (纸本)9781510663350

At present, apple disease control mainly relies on manual recognition, which causes a waste of human resources. In order to improve the efficiency of disease detection, this study focuses on apple leaf disease images in natural scenes. A lightweight network RepSSD consisting of feature extraction module, multi-scale feature recognition, and structural reparameterization is designed to detect apple leaf diseases. Replace the backbone part of the network with RepVGG-A0 without identity branch, and the auxiliary convolutional layer is replaced with a re-parameterized RepConv module without identity branch on top of the SSD. The CBAM attention mechanism module is also added to ensure adequate extraction of global features of apple leaf disease images in natural scenes. The experimental results show that the improved SSD has better detection accuracy and real-time performance in apple leaf disease recognition with an accuracy of 93.05%, which is 2.56% better than the original SSD, and the overall number of parameters decreases by 47.8%, the computation volume reduces by 86.7%, so the overall effect is better than the current common object detection models. Therefore, the algorithm can be better applied to apple disease control. Therefore, the model can be better used for apple disease control. © 2023 SPIE.

关键词： Disease control

来源：评论

学校读者我要写书评

暂无评论

EMOST: A dual-branch hybrid network for medical image fusion via efficient model module and sparse transformer

引用

Computers in Biology and Medicine 2024年 179卷 108771-108771页

作者： Wang, Wenqing He, Ji Liu, Han School of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

Multimodal medical image fusion fuses images with different modalities and provides more comprehensive and integrated diagnostic information. However, current multimodal image fusion methods cannot effectively model non-local contextual feature relationships, and due to direct aggregation of the extracted features, they introduce unnecessary implicit noise into the fused images. To solve the above problems, this paper proposes a novel dual-branch hybrid fusion network called EMOST for medical image fusion that combines a convolutional neural network (CNN) and a transformer. First, to extract more comprehensive feature information, an effective feature extraction module is proposed, which consists of an efficient dense block (EDB), an attention module (AM), a multiscale convolution block (MCB), and three sparse transformer blocks (STB). Meanwhile, a lightweight efficient model (EMO) is used in the feature extraction module to exploit the efficiency of the CNN with the dynamic modeling capability of the transformer. Additionally, the STB is incorporated to adaptively maintain the most useful self-attention values and remove as much redundant noise as possible by developing the top-k selection operator. Moreover, a novel feature fusion rule is designed to efficiently integrate the features. Experiments are conducted on four types of multimodal medical images. The proposed method shows higher performance than the art-of-the-state methods in terms of quantitative and qualitative evaluations. The code of the proposed method is available at https://***/XUTauto/EMOST. © 2024 Elsevier Ltd

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A mosquito mouthpart-like bionic neural probe

引用

Microsystems & Nanoengineering 2023年第4期9卷 77-90页

作者： Yu Zhou Huiran Yang Xueying Wang Heng Yang Ke Sun Zhitao Zhou Liuyang Sun Jianlong Zhao Tiger H.Tao Xiaoling Wei State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences200050 ShanghaiChina School of Graduate Study University of Chinese Academy of Sciences100049 BeijingChina 2020 X-Lab Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences200050 ShanghaiChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences100049 BeijingChina Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences200031 ShanghaiChina Neuroxess Co. Ltd.(Jiangxi)330029 NanchangJiangxiChina Guangdong Institute of Intelligence Science and Technology Hengqin519031 ZhuhaiGuangdongChina Tianqiao and Chrissy Chen Institute for Translational Research ShanghaiChina

Advancements in microscale electrode technology have revolutionized the field of neuroscience and clinicalapplications by offering high temporal and spatial resolution of recording and stimulation. Flexible neural probes, withtheir mechanical compliance to brain tissue, have been shown to be superior to rigid devices in terms of stability andlongevity in chronic recordings. Shuttle devices are commonly used to assist flexible probe implantation;however, theprotective membrane of the brain still makes penetration difficult. Hidden damage to brain vessels duringimplantation is a significant risk. Inspired by the anatomy of the mosquito mouthparts, we present a biomimeticneuroprobe system that integrates high-sensitivity sensors with a high-fidelity multichannel flexible electrode *** customizable system achieves distributed and minimally invasive implantation across brain regions. Mostimportantly, the system’s nonvisual monitoring capability provides an early warning detection for intracranial softtissues, such as vessels, reducing the potential for injury during implantation. The neural probe system demonstratesexceptional sensitivity and adaptability to environmental stimuli, as well as outstanding performance in postoperativeand chronic recordings. These findings suggest that our biomimetic neural-probe device offers promising potential forfuture applications in neuroscience and brain-machine interfaces.

关键词： neural implantation recording

来源：评论

学校读者我要写书评

暂无评论

Covert Communication in Satellite-Terrestrial systems with a Full-Duplex Receiver

Covert Communication in Satellite-Terrestrial Systems with a...

引用

2024 International Conference on Satellite Internet, SAT-NET 2024

作者： Guo, Zewei Sun, Ranran He, Ji Shen, Yulong Jiang, Xiaohong Future University Hakodate School of Systems Information Science Hakodate041-8655 Japan Hangzhou Institute of Technology Xidian University Hangzhou311200 China Xidian University School of Computer Science and Technology Xi'an710071 China Institute of Systems General Academy of Systems Engineering Academy of Military Sciences Beijing100101 China Xidian University Shaanxi Key Laboratory of Network and System Security Xi'an710071 China

ISBN: (纸本)9798350375176

This paper investigates the covert communication in a satellite-terrestrial system, including a satellite transmitter Alice, a terrestrial full-duplex receiver Bob and a terrestrial warden Willie. To help the covert transmission from Alice, the full-duplex Bob transmits the jamming signal to confuse Willie and also receives the signal from Alice simultaneously. To explore the fundamental covertness in such a system, we first provide theoretical modelings for satellite-terrestrial downlink, and the detection error probability of Willie. Based on these models, we then study the transmit power optimization for covert rate maximization. Finally, we present extensive numerical results to validate our theoretical analysis and to illustrate the impact of various system parameters on the maximum covert rate. © 2024 IEEE.

关键词： Satellite communication systems

来源：评论

学校读者我要写书评

暂无评论

Predicting Cell Line-Specific Synergistic Drug Combinations Through Siamese Network with Attention Mechanism 1

引用

2nd International Conference on Cognitive Computation and systems, ICCCS 2023

作者： Bao, Xin Chen, XiangYong Qiu, JianLong Wang, Donglin Qian, Xuewu Sun, JianQiang School of Information Science and Engineering Linyi University Linyi276005 China School of Automation and Electrical Engineering Linyi University Linyi276005 China Jinan Key Laboratory of 5G+ Advanced Control Technology Jinan250103 China

ISBN: (数字)9789819708857

ISBN: (纸本)9789819708840

Drug combination therapy holds great promise for curing cancer patients, as it can significantly enhance treatment effectiveness and reduce drug toxicity. However, efficiently identifying synergistic drug combinations from a vast pool of potential drug combinations remains challenging, mainly due to the expensive and time-consuming nature of traditional experimental methods. In this work, we introduce a novel deep learning method called SNAADC for discovering synergistic drug combinations. In SNAADC, we employ Siamese Network and attention mechanism to extract more effective drug features for better performance. The experimental results demonstrate that SNAADC outperforms traditional and popular methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Robust nanoporous Cu/TiO_(2) ceramic filter membrane with promoted bactericidal function

引用

science China(Technological sciences) 2022年第11期65卷 2687-2694页

作者： ZHOU Li SHI ChunYing XU XiaoHong JIA ChuanCheng Center of Single-Molecule Sciences Institute of Modern OpticsFrontiers Science Center for New Organic Matter Tianjin Key Laboratory of Micro-scale Optical Information Science and TechnologyCollege of Electronic Information and Optical EngineeringNankai UniversityTianjin300350.China School of Chemistry and Chemical Enginering Shandong UniversityJinan 250100China

Filter membrane technology has been extensively used for water ***,due to their high brittleness and biological fouling,filter membranes will gradually *** we develop a robust Cu/TiO_(2) ceramic filter membrane for water treatment,which has excellent inherent antibacterial activities both in the dark and under visible light *** nanobelt TiO_(2) can be sintered into a nanoporous membrane structure by overlapping and interweaving with each other,thereby achieving high flux simultaneously and solving the problem of high brittleness of inorganic ***,such one-dimensional TiO_(2) nanostructures can provide more deposition sites for Cu nanoparticles with inherent antibacterial activity in the *** realise the surface plasmon resonance-enhanced antibacterial activity under visible light,Cu/TiO_(2) heterostructures are used.

关键词： filter membrane one-dimensional TiO_(2) Cu/TiO_(2)heterostructure antibacterial activity

来源：评论

学校读者我要写书评

暂无评论

A Survey on Machine Learning-based Detection and Classification technology of Malware 4

A Survey on Machine Learning-based Detection and Classificat...

引用

4th International Conference on Computer information science and Artificial Intelligence, CISAI 2021

作者： Meng, Yangyang Zhuang, Honglin Lin, Zhechao Jia, Yetao AMS. PLA Institute of System Engineering Beijing China National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9781665406925

Under the background of massive malware, traditional methods of malware analysis can no longer efficiently meet the task of malware analysis. The development of machine learning technologies has effectively solved this problem. In recent years, machine learning and deep learning technologies have been gradually applied to the detection of malicious software. Machine learning-based malware classification has become a research hotspot in the field of malware detection. As an overview of machine learning-based detection and classification of malware, we analyze and summarize the system framework of malware detection and classification, introduce the basic categories of malware features and main classifiers of malware detection and classification, and propose a basic framework and technical architecture of feature processing technologies. Then, we summarize some issues and challenges faced by the current malware detection-related work. Finally, we discuss some potential research directions of machine learning-based detection and classification of malware from three aspects. © 2021 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Injecting spectral indices to transferable convolutional neural network under imbalanced and noisy labels for Landsat image classification

引用

International Journal of Digital Earth 2022年第1期15卷 437-462页

作者： Xuemei Zhao Jun Wu Haijian Wang Xingyu Gao Longlong Zhao School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuangxiPeople's Republic of China Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology School of Mechanical and Electrical EngineeringGuilin University of Electronic TechnologyGuangxiPeople's Republic of China Center for Geospatial Information Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesBeijingPeople's Republic of China

Stable and continuous remote sensing land-cover mapping is important for agriculture,ecosystems,and land *** neural networks(CNNs)are promising methods for achieving this ***,the large number of high-quality training samples required to train a CNN is difficult to *** practice,imbalanced and noisy labels originating from existing land-cover maps can be used as *** have shown that the inconsistency in the training samples has a significant impact on the performance of the *** overcome this drawback,a method is proposed to inject highly consistent information into the network,to learn general and transferable features to alleviate the impact of imperfect training *** indices are important features that can provide consistent *** indices can be fused with CNN feature maps which utilize information entropy to choose the most appropriate CNN layer,to compensate for the inconsistency caused by the imbalanced,noisy *** proposed transferable CNN,tested with imbalanced and noisy labels for inter-regional Landsat time-series,not only is superior in terms of accuracy for land-cover mapping but also demonstrates excellent transferability between regions in both time series and cross-regional Landsat image classification.

关键词： Landsat image classification imbalanced and noisy label convolutional neural network(CNN) transferability feature fusion information entropy

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：