检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Pan, Han-Yang Yang, Qiang Li, Ming Zhang, En Ma, Yuan-Yuan Li, Tao Liu, Dong Zhang, Jun College of Computer and Information Engineering Henan Normal University Xinxiang China Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province Xinxiang China School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing China Zhejiang Normal University Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Jinhua China Hanyang University Department of Electrical and Electronic Engineering Ansan Korea Republic of

ISBN: (纸本)9798350337020

This paper proposes a stochastic dominant cognitive experience-guided learning framework for particle swarm optimization (SDCEGPSO) to enhance its search ability in complex environment. Specifically, different from classical PSOs, SDCEGPSO randomly selects dominant cognitive experiences to guide the learning of particles. To this end, the cognitive experiences of all particles, namely their personal best positions, are sorted from the best to the worst. Then, each particle randomly chooses a personal best position better than its own to learn. For the cognitive experience selection, this paper designs three selection methods, namely the random selection, the roulette wheel selection, and the tournament selection. With this learning framework, particles have diverse guiding exemplars to learn from and thus high search diversity is expectedly maintained. Experiments conducted on the 50-D and 100-D CEC2014 problem suite have verified the effectiveness of SDCEGPSO. Compared with the classical global PSO (GPSO) and local PSO (LPSO), SDCEGPSO with the three selection schemes achieve significantly better performance. Besides, among the three selection schemes, the binary tournament selection is the most effective one to help SDCEGPSO solve optimization problems. © 2023 IEEE.

关键词： Evolutionary Algorithms Global Optimization Particle Swarm Optimization Stochastic Dominant Cognitive Experience Guided Learning

来源：评论

学校读者我要写书评

暂无评论

BREAKING SPEAKER RECOGNITION WITH PADDINGBACK

arXiv

引用

arXiv 2023年

作者： Ye, Zhe Yan, Diqun Dong, Li Shen, Kailai Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology China

Machine Learning as a Service (MLaaS) has gained popularity due to advancements in Deep Neural Networks (DNNs). However, untrusted third-party platforms have raised concerns about AI security, particularly in backdoor attacks. Recent research has shown that speech backdoors can utilize transformations as triggers, similar to image backdoors. However, human ears can easily be aware of these transformations, leading to suspicion. In this paper, we propose PaddingBack, an inaudible backdoor attack that utilizes malicious operations to generate poisoned samples, rendering them indistinguishable from clean ones. Instead of using external perturbations as triggers, we exploit the widely-used speech signal operation, padding, to break speaker recognition systems. Experimental results demonstrate the effectiveness of our method, achieving a significant attack success rate while retaining benign accuracy. Furthermore, PaddingBack demonstrates the ability to resist defense methods and maintain its stealthiness against human perception. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Research on Ornamental Fish Recognition Base on Improved Shufflenet V2 Network 4

Research on Ornamental Fish Recognition Base on Improved Shu...

引用

4th International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2023

作者： Zhang, Xingyun Chen, Hongming Zhang, Longqing Chen, Qian Zhejiang Ocean University Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhoushan316022 China Guangdong University of Science and Technology School of Computer Science Dongguan523083 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China

ISBN: (纸本)9798350329490

With the advancement of computer vision technology, fish recognition plays a crucial role in various fields such as aquaculture processing and disseminating fish knowledge. In this study, we propose an enhanced and lightweight fish recognition algorithm to accomplish fish classification recognition with limited data samples. Based on the ShuffleNet V2 network, we incorporate Transfer Learning and the SE attention mechanism. Additionally, we replace the ReLu activation function with the AM-Softmax activation function. Comparative evaluations are conducted against Resnet50, MobileNet V2, MobileNet V3, and the original ShuffleNet V2 network model. Our experimental findings demonstrate that the proposed algorithm outperforms the aforementioned models, resulting in recognition accuracy improvements of 16.01%, 19.05%, 15.04%, and 14.44% respectively. The final recognition accuracy achieved is 97.20%, successfully attaining the desired outcome. © 2023 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Research on Brightness Compensation Algorithm for GF-3 SAR Images 7th

Research on Brightness Compensation Algorithm for GF-3 SAR I...

引用

7th China High-resolution Earth Observation Conference, CHREOC 2020

作者： Sun, Zengguo Yan, Xiaopeng Chen, Qianfu Chen, Weirong Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an China School of Computer Science Shaanxi Normal University Xi’an China Land Satellite Remote Sensing Application Center MNR Beijing China China Centre for Resources Satellite Data and Application Beijing China

ISBN: (纸本)9789811657344

GF-3, the first C-Band full-polarimetric synthetic aperture radar (SAR) satellite with a space resolution up to 1 m, has multiple strip and scan imaging modes. In this paper, a brightness compensation model is proposed to correct the unbalanced radiation image of GF-3 satellite in some areas based on mathematical morphology principle, SAR imaging model, and histogram mapping model, so that the image radiation is relatively consistent and has moderate contrast. The proposed algorithm is tested on the GF-3 SAR image with radiation difference in Taklimakan desert area of Xinjiang, and is compared with the MASK dodging algorithm in terms of brightness mean, standard deviation, information entropy, and average gradient. Results of brightness compensation show that, the proposed algorithm makes the radiation differences within images smaller, and the image quality is obviously improved, which provides a non-radiation difference image for subsequent applications. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mathematical morphology

来源：评论

学校读者我要写书评

暂无评论

Specific Emitter Identification Based on ACGAN and STFT

Specific Emitter Identification Based on ACGAN and STFT

引用

Advanced Algorithms and Control Engineering (ICAACE), International Conference on

作者： Bin Wang Jun Xie Feng Wang The 38th Research Institute of China Electronics Technology Group Corporation Key Laboratory of Aperture Array and Space Application Key Laboratory of Intelligent Information Processing Hefei Anhui China School of Computer and Information Hefei University of Technology Hefei China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Deep learning methodologies are gaining popularity for enhancing the efficiency of Specific Emitter Identification (SEI). Nevertheless, the lack of labeled datasets continues to pose a challenge in most non-cooperative scenarios for SEI. Addressing this challenge, a framework for SEI is proposed, leveraging Short-Time Fourier Transform (STFT) in conjunction with auxiliary classifier GAN(ACGAN). The Short-Time Fourier Transform of emitters is utilized as radio-frequency fingerprint for the emitters. The input latent layer is infused with label information to steer the training process of the Generative Adversarial Network. Through semi-supervised training, shared weight updates are implemented for the classification network. Experimental results demonstrate that our model can achieve superior or competitive performances in several datasets compared with the former models.

关键词： Training Radio frequency Deep learning Fourier transforms Control engineering Fingerprint recognition Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Step-by-Step: Controlling Arbitrary Style in Text with Large Language Models 30

Step-by-Step: Controlling Arbitrary Style in Text with Large...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Pusheng Wu, Lianwei Wang, Linyong Guo, Sensen Liu, Yang National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University China Research & Development Institute of Northwestern Polytechnical University Shenzhen China Chongqing Science & Technology Innovation Center of Northwestern Polytechnical University China State Key Laboratory of Integrated Service Networks Xidian University China School of Artificial Intelligence Optics and Electronics Northwestern Polytechnical University China

ISBN: (纸本)9782493814104

Recently, the autoregressive framework based on large language models (LLMs) has achieved excellent performance in controlling the generated text to adhere to the required style. These methods guide LLMs through prompt learning to generate target text in an autoregressive manner. However, this manner possesses lower controllability and suffers from the challenge of accumulating errors, where early prediction inaccuracies might influence subsequent word generation. Furthermore, existing prompt-based methods overlook specific region editing, resulting in a deficiency of localized control over input text. To overcome these challenges, we propose a novel three-stage prompt-based approach for specific region editing. To alleviate the issue of accumulating errors, we transform the text style transfer task into a text infilling task, guiding the LLMs to modify only a small portion of text within the editing region to achieve style transfer, thus reducing the number of autoregressive iterations. To achieve an effective specific editing region, we adopt both prompt-based and word frequency-based strategies for region selection, subsequently employing a discriminator to validate the efficacy of the selected region. Experiments conducted on several publicly competitive datasets for text style transfer task confirm that our proposed approach achieves state-of-the-art performance. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

LabelEase: A Semi-Automatic Tool for Efficient and Accurate Trace Labeling in Microservices

LabelEase: A Semi-Automatic Tool for Efficient and Accurate ...

引用

International Symposium on Software Reliability Engineering (ISSRE)

作者： Shenglin Zhang Zeyu Che Zhongjie Pan Xiaohui Nie Yongqian Sun Lemeng Pan Dan Pei Nankai University Haihe Laboratory of Information Technology Application Innovation Computer Network Information Center Chinese Academy of Sciences Tianjin Key Laboratory of Software Experience and Human Computer Interaction Huawei Beijing National Research Center for Information Science and Technology Tsinghua University

ISBN: (数字)9798350353884

ISBN: (纸本)9798350353891

Trace data is crucial for system observability and maintainability within microservices architectures, and many operation algorithms depend heavily on trace data, including anomaly detection, root cause analysis, etc. However, the actual performance of these algorithms might be unsatisfactory due to the absence of high-quality labeled datasets for effective training and evaluation. Since billions of traces could be generated daily for large-scale microservices, labeling overhead is the main hurdle to obtaining high-quality trace *** this paper, we propose LabelEase, a novel semi-automatic trace labeling tool, which uses active learning techniques to achieve efficient and accurate trace labeling. For anomaly trace labeling, LabelEase clusters similar traces with a graph-based trace representation technique and selects a few representative traces for human labeling, avoiding labeling most of the traces. For root cause labeling, LabelEase aggregates the labeled anomalous traces and identifies the service’s failures for operators to label. Our systematic experiments on two large-scale datasets show that LabelEase achieves over 0.98 F 1 -score in anomaly trace labeling and 0.89 precision of failure detection in root cause labeling, LabelEase can reduce operators’ labeling overhead by more than 99.9%. To the best of our knowledge, we are the first to propose a semi-automatic trace labeling tool capable of achieving efficient and accurate trace labeling.

关键词： Training Location awareness Accuracy Costs Transfer learning Microservice architectures Manuals Data models Labeling Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Dependency and Association Enhanced Finding Similar Exercises in Online Education System 8

Dependency and Association Enhanced Finding Similar Exercise...

引用

8th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2022

作者： Tang, Zihang Wang, Hao Gao, Weibo Huang, Zhenya Liu, Qi Yu, Jun University of Science and Technology of China School of Data Science China University of Science and Technology of China Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Technology China IFLYTEK CO. LTD. IFLYTEK Research

ISBN: (纸本)9781665477352

Finding Similar Exercises (FSE) is a tough nut to crack in online education systems, especially among large scale exercise corpus. Given exercises with associated attributes, contents (texts and images) and knowledge concepts, most solutions learn exercise representations in isolation, where only contents or concepts are exploited. Though a few works try to combine concept-exercise associations for capturing long-range similarity among exercises, they just utilize a single relation among concepts but neglect the multiple dependencies. In this paper, we propose a novel Dependency and Association enhanced Finding Similar Exercises framework, namely DAFSE, which can consider both the concept-exercise associations and the multiple dependency relations among concepts, simultaneously. Specifically, we first build a concept-exercise-content multi-layer graph and embed each concept, exercise and content node through an Embedding Layer. Then we introduce Attentive Combination Layer to effectively preserve the long-range similarity as well as rich domain knowledge to exercise representations by propagating on the multi-layer graph. Finally, we use a Similarity Score Layer to assess the similarity of exercise pairs. Extensive experiments on real-world datasets demonstrate the effectiveness of DAFSE. © 2022 IEEE.

关键词： Online systems

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of AS6802 Clock Synchronization System in TTE thernet 6

Design and Implementation of AS6802 Clock Synchronization Sy...

引用

6th IEEE International Conference on computer and Communication Systems, ICCCS 2021

作者： Dong, Jinlong Qiu, Zhiliang Pan, Weitao Wu, Min Cao, Jialiang State Key Laboratory of the Integrated Services Networks Xidian University Xi'an710071 China Beijing Institute of Computer Technology and Application

ISBN: (纸本)9780738126043

Based on the research of the standard AS6802 protocol standard [1] and the interpretation of the existing Ethernet time synchronization solution on the FPGA hardware design platform, we designed and implemented a set of Ethernet clock synchronization system that supports the AS6802 standard. The system has been tested in a network environment, and the synchronization accuracy is less than 60 nanoseconds. Use FPGA to record the transparent clock, replacing the MAC IP core time stamping method in the previous Ethernet time synchronization solution. Therefore, this system is more flexible for the reception and transmission of Ethernet frame data, and reduces the dynamic delay introduced by the MAC IP core, which makes the synchronization accuracy higher, and has the characteristics of low cost and easy transplantation. © 2021 IEEE.

关键词： Field programmable gate arrays (FPGA)

来源：评论

学校读者我要写书评

暂无评论

High Wind Speed Retrieval from SAR Images Using Random Forest Algorithm

High Wind Speed Retrieval from SAR Images Using Random Fores...

引用

2023 International Conference on Remote Sensing, Mapping, and Geographic Systems, RSMG 2023

作者： Yang, Wenjin Yu, Peng Cai, Xiaoying Zhong, Xiaojing He, Yuanrong College of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Key Laboratory of Space Ocean Remote Sensing and Application Ministry of Natural Resources P.R. China Beijing100081 China College of Harbour and Coastal Engineering Jimei University Xiamen361021 China

ISBN: (纸本)9781510668898

This study provides a random forest (RF) based method to retrieve high wind speeds, which takes advantage of RF's powerful nonlinear fitting ability and prevents overfitting. The high wind speed data from the Stepping Frequency Microwave Radiometer (SFMR) are used as the reference data. Compared with two traditional GMF models, the C-band cross-polarized ocean model (C-2PO) and the C-band cross-polarized coupled parameter ocean model (C-3PO), the wind speed inversion results using the RF method have been greatly improved. © 2023 SPIE.

关键词： Synthetic aperture radar

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：