检索结果-内蒙古大学图书馆

15th International Conference on information Optics and Photonics, CIOP 2024

作者： Jiang, Xiaowen Deng, Hongchang Qu, Shiliang Guangxi Key Laboratory of Optoelectronic Information Processing School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin541004 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

A novel SPR fiber-optic sensor for highly sensitive surrounding refractive index (SRI) detection is proposed and experimentally demonstrated. The sensor is composed of a graded-index multimode - tapered capillary - graded-index multimode optical fiber (GIF-TCOF-GIF) structure with a 50nm gold layer coated on one side of the sensitive section. For the sensor immersed in a liquid sample, the SPR valley shows up at a wavelength around 600 nm. Changes of surrounding refractive index led to a red shift of the SPR valley wavelength. Benefitting from the higher order modes excited by the tapered capillary propagating in the silica cladding, the proposed sensor achieves a higher refractive index sensitivity of 6729.4 nm/RIU at a RI of 1.4195, which beyond many other previous works with cascaded structures. Experimental results show that this proposed sensor also has the advantages of small size, ease of fabrication process, low temperature crosstalk and lower cost, which make it ideal for practical bio-sensing and chemical sensing applications. © 2024 SPIE.

关键词： Silica

来源：评论

学校读者我要写书评

暂无评论

Gland segmentation based on morphological clues and feature fusion 2

Gland segmentation based on morphological clues and feature ...

引用

2nd International Conference on Image processing, Computer Vision and Machine Learning, ICICML 2023

作者： Zeng, Lingqi Wang, Huadeng Guan, Junlin Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin541004 China

ISBN: (纸本)9798350331417

The task of gland segmentation based on deep learning serves as a crucial auxiliary tool for diagnosing cancer. However, existing methods still exhibit shortcomings in handling gland adhesion and scale adaptability. To address these issues, we propose a gland segmentation approach that leverages morphological cues and multi-level feature fusion. By analyzing the morphological and imaging characteristics of glands, we have devised a novel scheme for label generation and loss weighting to guide model training. This scheme helps alleviate the challenge posed by the presence of adjacent glands and their adhesion. Additionally, by exploring the correlation between semantic features at different levels, we have developed a new feature fusion mechanism to mitigate issues related to model inaccuracies arising from variations in gland scales. Through experimental comparisons and discussions with classical and state-of-the-art methods, we demonstrate the effectiveness of our proposed approach. © 2023 IEEE.

关键词： Feature fusion Gland segmentation Morphological cues Multi-level feature

来源：评论

学校读者我要写书评

暂无评论

Weakly-Supervised Graph Classification with Even a Single key Subgraph Per Class 24

Weakly-Supervised Graph Classification with Even a Single Ke...

引用

24th IEEE International Conference on Data Mining, ICDM 2024

作者： Zhang, Lu Zhang, Chenbo Guan, Jihong Zhou, Shuigeng School of Computer Science Fudan University Shanghai Key Lab of Intelligent Information Processing China Tongji University Department of Computer Science & Technology China

ISBN: (纸本)9798331506681

Traditional graph classification requires large amounts of labeled data, which is expensive and time-consuming to acquire, especially in some special scenarios that domain knowledge is indispensable for labeling graphs. Observing that some key subgraphs can determine the properties of graphs (e.g. the toxicity of drug molecules depend on some toxic functional groups), in this paper we explore to classify graphs using unlabeled graphs plus a small number of key subgraphs for each class, which is called weakly-supervised graph classification. To this end, we develop the WeGraph method, where the graph classifier is trained with subgraph-based self-supervised learning and divergence- minimization based fine-tuning. Moreover, we design a key subgraph extraction algorithm to iteratively extract and update the key subgraphs, which makes the training process a closed loop. We conduct extensive experiments on different types of graph datasets to evaluate the effectiveness of WeGraph. Experimental results show that WeGraph can achieve high performance even when only one key subgraph is provided for each class. © 2024 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

A Small-sample Trajectory Classification Algorithm via Bayesian Program Learning

A Small-sample Trajectory Classification Algorithm via Bayes...

引用

International Conference on Signal processing Proceedings (ICSP)

作者： Yanshan Li Ruoqiang Yao Institute of Intelligent Information Processing Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China Institute of Intelligent Information Processing Shenzhen University Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Trajectory classification algorithms are widely used in fields such as behavior recognition, anomaly detection and monitoring, and video content analysis. To overcome the issues of traditional trajectory classification algorithms that require large supporting data and continuous model updates to ensure effectiveness, we take inspiration from the concept learning approach proposed by Brenden et al. We simulate how humans learn rich concepts from a single hand-drawn sample and propose a Bayesian program learning-based trajectory classification algorithm. This algorithm first builds concepts from a set of hand-drawn trajectories and then classifies trajectory data based on these constructed concepts. Experimental results show that our algorithm outperforms traditional single-sample learning algorithms in trajectory classification tasks and also shows superior performance over traditional single-sample learning algorithms when the dataset includes noisy data.

关键词： Content management Noise Signal processing algorithms Programming Data models Trajectory Classification algorithms Bayes methods Noise measurement Monitoring

来源：评论

学校读者我要写书评

暂无评论

Acute Observational Stimulus of Restrained Mice Induced Anxiolytic Effects in Observer Mice

引用

Neuroscience Bulletin 2024年第10期40卷 1545-1550页

作者： Chun-Hui Jia Fang-Qi Shu Pak-Ming Lau Hao Wang CAS Key Laboratory of Brain Function and Disease Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefei 230026China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefei 230088China Interdisciplinary Center for Brain Information The Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China National Engineering Laboratory for Brain-inspired Intelligence Technology and Application School of Information Science and TechnologyUniversity of Science and Technology of ChinaHefei 230026China

Dear Editor,Ensuring an appropriate response to external stimuli is essential for animals'survival and *** indicates that such stimuli can affect animals'physiological state and hormone levels,including corticosterone(CORT)[1,2].The impact of these stimuli on animals'performance depends on their density and duration,as they can either facilitate or hinder *** chronic and intense stressors can have detrimental effects on animals'physiological health and behavioral performance,leading to psychiatric disorders such as depression,anxiety,and schizophrenia[3],the effects of acute and mild observational stimuli are still unclear.

关键词： evolution. Observation acute

来源：评论

学校读者我要写书评

暂无评论

A Bayesian matrix factorization model for dynamic user embedding in recommender system

引用

Frontiers of Computer Science 2022年第5期16卷 233-235页

作者： Kaihan ZHANG Zhiqiang WANG Jiye LIANG Xingwang ZHAO Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information TechnologyShanxi UniversityTaiyuan 030006China

1 Introduction The main idea of recommender system is how to learn accurate users’embeddings from behavior data[1].Each dimension of users’embeddings can reflect the interests of users in different potential *** real-world scenarios,users’interests are drifting over time,which brings a challenge to learn accurate dynamic users’***,various time-aware recommendation methods have been proposed to tackle this problem by modeling the evolution process of users’interests[2−4].However,they usually assume that users’embeddings drift with the same range on all *** practice,users’embeddings should change diversely on different dimensions over ***,for the rapidly changing interests of the users,the corresponding dimensions should change *** the contrary,the dimensions representing stable interests may change slightly.

关键词： dimensions system dynamic

来源：评论

学校读者我要写书评

暂无评论

GAN-based Fusion of Infrared and Visible Images in Dark Light Environments

GAN-based Fusion of Infrared and Visible Images in Dark Ligh...

引用

2024 China Automation Congress, CAC 2024

作者： Shi, Jiaoxing Chen, Yanfei Li, Haiming Yang, Lei Liu, Yangkai Yue, Tong Hubei Key Laboratory of Intelligent Robot School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (纸本)9798350368604

In low light conditions, the fused image generated by fusion of infrared and visible images is dark and lacks detailed texture information, resulting in low target detection accuracy, based on which a target detection network for fusion of infrared and visible images in low light conditions is proposed. Firstly, the dark light perception network is designed to enhance the brightness of the dark light image;secondly, the feature extraction module of the image fusion network introduces the gradient residual dense block to strengthen the ability of the image fusion network to extract the depth features and fine-grained detail features of the source image;subsequently, the loss function incorporates the intensity loss and the structural similarity loss to enhance the ability of the image fusion network to extract the pixel intensities and the structural texture details of the source image;Finally, the optimal solution of the fusion network for target detection is achieved by joint training of the image fusion network and the target detection network. The experimental results show that the fusion network in the paper improves the mutual information, average gradient, visual fidelity, gradient-based fusion performance, and structural similarity by 0.142, 0.135, 0.043, 0.067, and 0.082 compared to the other network models, and improves the average precision mean and accuracy by 2.6% and 2.5%, respectively, in the YOLOV8 detection network. © 2024 IEEE.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

The Detection of Fraudulent Smart Contracts Based on ECA-EfficientNet and Data Enhancement

引用

Computers, Materials & Continua 2023年第12期77卷 4073-4087页

作者： Xuanchen Zhou Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Software Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region Urumqi830000China Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region Urumqi830000China

With the increasing popularity of Ethereum,smart contracts have become a prime target for fraudulent activities such as Ponzi,honeypot,gambling,and phishing *** some researchers have studied intelligent fraud detection,most research has focused on identifying Ponzi contracts,with little attention given to detecting and preventing gambling or phishing *** are three main issues with current ***,there exists a severe data imbalance between fraudulent and non-fraudulent ***,the existing detection methods rely on diverse raw features that may not generalize well in identifying various classes of fraudulent ***,most prior studies have used contract source code as raw features,but many smart contracts only exist in *** address these issues,we propose a fraud detection method that utilizes Efficient Channel Attention EfficientNet(ECA-EfficientNet)and data *** method begins by converting bytecode into Red Green Blue(RGB)three-channel images and then applying channel exchange data *** then use the enhanced ECA-EfficientNet approach to classify fraudulent smart contract RGB *** proposed method achieves high F1-score and Recall on both publicly available Ponzi datasets and self-built multi-classification datasets that include Ponzi,honeypot,gambling,and phishing smart *** results of the experiments demonstrate that our model outperforms current methods and their variants in Ponzi contract *** research addresses a significant problem in smart contract security and offers an effective and efficient solution for detecting fraudulent contracts.

关键词： Fraud detection smart contract ECA-EfficientNet Ethereum

来源：评论

学校读者我要写书评

暂无评论

Dual-band All-optical Logic Gate Based on Coherent Control Principles

Dual-band All-optical Logic Gate Based on Coherent Control P...

引用

2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Shi, Xinyu Chen, Ming Zhao, Wanli Han, Wenhao Guilin University of Electronic Technology Guangxi Key Laboratory of Optoelectronic Information Processing School of Optoelectronic Engineering Guilin541004 China

ISBN: (纸本)9798350375909

Over the past two decades, all-optical signal processing technology based on photonics circuits has presented extremely high data processing speeds. The use of light controlled light to achieve various functional devices has aroused great interest among researchers. All-optical logic gates are indispensable in optical signal processing and optical networks. In this article, we introduce some design and research on coherent light control characteristics based on metasurface and propose dual band metasurface all-optical logic gates based on the coherent modulation principle. By designing a meta-surface structure that excites the Pseudo-Anapole effect, coherent perfect absorption and coherent perfect transmission are achieved at operating wavelengths of 1310 nm and 1550 nm. By controlling the phase difference between coherent beams, modulation of the total output is achieved, and appropriate threshold strength is set to achieve logic gating functions such as AND, OR, and XOR. The concept of contrast is introduced to quantitatively analyze the performance of logic gates. Compared to traditional all-optical logic gates, the proposed device has the advantages of high contrast ratio (14.13 dB) and ultra-short switching time, as well as a simple structure and wide application range. © 2024 IEEE.

关键词： Optical signal processing

来源：评论

学校读者我要写书评

暂无评论

GRATDet:Smart Contract Vulnerability Detector Based on Graph Representation and Transformer

引用

Computers, Materials & Continua 2023年第8期76卷 1439-1462页

作者： Peng Gong Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Information Science and Engineering Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region Xinjiang UniversityUrumqi830000China Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region Xinjiang UniversityUrumqi830000China

Smart contracts have led to more efficient development in finance and healthcare,but vulnerabilities in contracts pose high risks to their future *** current vulnerability detection methods for contracts are either based on fixed expert rules,which are inefficient,or rely on simplistic deep learning techniques that do not fully leverage contract semantic ***,there is ample room for improvement in terms of detection *** solve these problems,this paper proposes a vulnerability detector based on deep learning techniques,graph representation,and Transformer,called *** method first performs swapping,insertion,and symbolization operations for contract functions,increasing the amount of small sample *** line of code is then treated as a basic semantic element,and information such as control and data relationships is extracted to construct a new representation in the form of a Line Graph(LG),which shows more structural features that differ from the serialized presentation of the ***,the node information and edge information of the graph are jointly learned using an improved Transformer-GP model to extract information globally and locally,and the fused features are used for vulnerability *** effectiveness of the method in reentrancy vulnerability detection is verified in experiments,where the F1 score reaches 95.16%,exceeding stateof-the-art methods.

关键词： Vulnerability detection smart contract graph representation deep learning source code

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：