检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Sensors, Electronics and computer Engineering, ICSECE 2023

作者： Liang, Tianmian Li, Peng Cao, Yumei Wu, Xiaojun Zhao, Huifang Qi, Chenye School of Computer Science Shaanxi Normal University Xi'an710119 China Shaanxi Normal University School of Computer Science Xi'an710119 China Ministry of Education Key Laboratory of Modern Teaching Technology Xi'an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi'an710119 China Xi'An Key Laboratory of Cultural Tourism Resources Development and Utilization Xi'an710062 China Shaanxi Normal University School of Music Xi'an710119 China

ISBN: (纸本)9798350313734

Currently most AI music generator platforms mainly focus on creating modern music, without focusing on the creation of folk music. And most music generation neural network models use recursive neural networks and their variants, resulting in excessively repetitive music information, greatly reducing the fun of music. When using only generative adversarial networks (GANs) to generate music, it is easy to experience unstable training, vanishing gradients, and mode collapse. Failure to consider time dependence can reduce the authenticity of generated music. In order to solve the problem that most of the conventional deep learning GAN music generation network models do not consider music theory rules in music generation and Xi'an drum music faces the scarcity of tracks and difficulties in composition, we proposed a GAN network music generative model based on music theory rules and characteristics of Chinese Folk Songs. When generating music, the generator CNN and the regulator CNN train together, and generate music melodies under the constraints of the voice column CNN module. The generated results are sent to the discriminator CNN, which submits feedback to the generator CNN for competition, to compensate for the shortcomings of previous technology and ultimately generate better melodies, thereby improving the authenticity, sweetness, and rhythm of the generated music. © 2023 IEEE.

关键词： Music

来源：评论

学校读者我要写书评

暂无评论

Deformation Field Component Attention Fusion for Coarse-to-Fine Medical Image Registration Network 9

Deformation Field Component Attention Fusion for Coarse-to-F...

引用

9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Zhang, Chi Zhao, Haifeng Liu, Deyin School of Computer Science and Technology Institute of Artificial Intelligence Hefei Comprehensive National Science Center Anhui University Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Hefei China School of Artificial Intelligence Anhui University Hefei China

ISBN: (纸本)9798350376548

In recent years, deep learning-based medical image registration algorithms have demonstrated notable achievements in improving registration accuracy and speed. However, these algorithms have not explored the potential benefits of utilizing different networks to generate distinct deformation fields, which can then be integrated to produce a final deformation field. In this paper, we propose deformation field component attention fusion for coarse-to-fine medical image registration. Specifically, the registration process is divided into multiple stages, which generate different deformation fields that focus on capturing deformations of varying degrees. To ensure the effective integration of multiple deformation fields, we propose the Deformation Field Component Attention Fusion Module. This module separates the deformation field into three axial displacement components and performs independent attention fusion for the different axial displacement components. Through comparative experiments and ablation studies, we demonstrate the effectiveness of the proposed method. © 2024 IEEE.

关键词： Image registration

来源：评论

学校读者我要写书评

暂无评论

A Gradient-Guided Evolutionary Approach to Training Deep Neural networks

引用

IEEE TRANSACTIONS ON NEURAL networks AND LEARNING SYSTEMS 2022年第9期33卷 4861-4875页

作者： Yang, Shangshang Tian, Ye He, Cheng Zhang, Xingyi Tan, Kay Chen Jin, Yaochu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei China Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Department of Computing The Hong Kong Polytechnic University Hong Kong SAR Department of Computer Science University of Surrey Guildford U.K

It has been widely recognized that the efficient training of neural networks (NNs) is crucial to classification performance. While a series of gradient-based approaches have been extensively developed, they are criticized for the ease of trapping into local optima and sensitivity to hyperparameters. Due to the high robustness and wide applicability, evolutionary algorithms (EAs) have been regarded as a promising alternative for training NNs in recent years. However, EAs suffer from the curse of dimensionality and are inefficient in training deep NNs (DNNs). By inheriting the advantages of both the gradient-based approaches and EAs, this article proposes a gradient-guided evolutionary approach to train DNNs. The proposed approach suggests a novel genetic operator to optimize the weights in the search space, where the search direction is determined by the gradient of weights. Moreover, the network sparsity is considered in the proposed approach, which highly reduces the network complexity and alleviates overfitting. Experimental results on single-layer NNs, deep-layer NNs, recurrent NNs, and convolutional NNs (CNNs) demonstrate the effectiveness of the proposed approach. In short, this work not only introduces a novel approach for training DNNs but also enhances the performance of EAs in solving large-scale optimization problems.

关键词： Artificial neural networks Training Optimization Search problems Scalability Complexity theory Genetic algorithms Deep neural networks (DNNs) evolutionary algorithm (EA) genetic operator gradient descent sparsity

来源：评论

学校读者我要写书评

暂无评论

WFSS: weighted fusion of spectral transformer and spatial self-attention for robust hyperspectral image classification against adversarial attacks

引用

Visual Intelligence 2024年第1期2卷 1-16页

作者： Tang, Lichun Yin, Zhaoxia Su, Hang Lyu, Wanli Luo, Bin Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Anhui China School of Communication & Electronic Engineering East China Normal University Shanghai China Department of Computer Science and Technology Tsinghua University Beijing China

The emergence of adversarial examples poses a significant challenge to hyperspectral image (HSI) classification, as they can attack deep neural network-based models. Recent adversarial defense research tends to establish global connections of spatial pixels to resist adversarial attacks. However, it cannot yield satisfactory results when only spatial pixel information is used. Starting from the premise that the spectral band is equally important for HSI classification, this paper explores the impact of spectral information on model robustness. We aim to discover potential relationships between different spectral bands and establish global connections to resist adversarial attacks. We design a spectral transformer based on the transformer structure to model long-distance dependency relationships among spectral bands. Additionally, we use a self-attention mechanism in the spatial domain to develop global relationships among spatial pixels. Based on the above framework, we further explore the influence of both spectral and spatial domains on the robustness of the model against adversarial attacks. Specifically, a weighted fusion of spectral transformer and spatial self-attention (WFSS) is designed to achieve the multi-scale fusion of spectral and spatial connections, which further improves the model’s robustness. Comprehensive experiments on three benchmarks show that the WFSS framework has superior defensive capabilities compared to state-of-the-art HSI classification methods. © The Author(s) 2024.

关键词： Adversarial attack Adversarial example Hyperspectral image (HSI) classification Self-attention Transformer

来源：评论

学校读者我要写书评

暂无评论

Drosophila Larvae-Inspired Soft Crawling Robot with Multimodal Locomotion and Versatile Applications

引用

Research 2025年第1期7卷 35-46页

作者： Qin Fang Jingyu Zhang Yinhui He Nenggan Zheng Yue Wang Rong Xiong Zhefeng Gong Haojian Lu State Key Laboratory of Industrial Control and Technology Zhejiang UniversityHangzhou 310027China Institute of Cyber-Systems and Control Zhejiang UniversityHangzhou 310027China Medical School of Zhejiang University Hangzhou 310027China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Stomatology Hospital School of StomatologyZhejiang University School of MedicineZhejiang Provincial Clinical Research Center for Oral DiseasesKey Laboratory of Oral Biomedical Research of Zhejiang ProvinceCancer Center of Zhejiang UniversityEngineering Research Center of Oral Biomaterials and Devices of Zhejiang ProvinceHangzhou 310000China

Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible ***,most existing soft crawling robots typically exhibit a single-motion mode and lack diverse *** by Drosophila larvae,this paper proposes a compact soft crawling robot(weight,13 g;length,165 mm;diameter,35 mm)with multimodal locomotion(forward,turning,rolling,and twisting).Each robot module uses 4 sets of high-power-density shape memory alloy actuators,endowing it with 4 degrees of motion *** analyze the mechanical characteristics of the robot modules through experiments and simulation *** plug-and-play modules can be quickly assembled to meet different motion and task *** soft crawling robot can be remotely operated with an external controller,showcasing multimodal motion on various material *** a narrow maze,the robot demonstrates agile movement and effective maneuvering around *** addition,leveraging the inherent bistable characteristics of the robot modules,we used the robot modules as anchoring units and installed a microcamera on the robot's head for pipeline *** robot completed the inspection in horizontal,vertical,curved,and branched pipelines,adjusted the camera view,and twisted a valve in the pipeline for the first *** research highlights the robot's superior locomotion and application capabilities,providing an innovative strategy for the development of lightweight,compact,and multifunctional soft crawling robots.

关键词： multimodal locomotion versatile applications Drosophila larvae soft crawling robot weight soft crawling robots shape memory alloy actuators

来源：评论

学校读者我要写书评

暂无评论

FindINT: Detect and Locate the Lost in-Band Network Telemetry Packet

IEEE Networking Letters

引用

IEEE Networking Letters 2022年第1期4卷 20-24页

作者： Tan, Lizhuang Su, Wei Miao, Jingying Zhang, Wei School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center National Supercomputer Center in ji'Nan Qilu University of Technology Shandong Academy of Sciences Ji'nan250000 China

In-band network telemetry (INT) is a new network measurement technology that uses business packet to collect network information hop by hop. Since business packets may be lost due to various reasons, INT telemetry information will inevitably be lost. Unfortunately, telemetry system is not aware of this loss. In this letter, we present FindINT, an INT packet coding scheme with two marking strategies, to measure per-flow packet loss rate and location. FindINT is inspired by alternative marking method, which is triggered by loss event instead of *** results show that FindINT has extremely low overhead and high detection accuracy. © 2019 IEEE.

关键词： Packet networks

来源：评论

学校读者我要写书评

暂无评论

Research and Application of Smart Water Meter Monitoring System Based on NB-IoT 7

Research and Application of Smart Water Meter Monitoring Sys...

引用

7th IEEE Information technology and Mechatronics Engineering Conference, ITOEC 2023

作者： Zhao, Yuanyuan Zhang, Tixiang Hao, Huijuan Zhang, Xiaojie Shandong Computer Science Center Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science No. 19 Keyuan Road Shandong Jinan250014 China Shandong Yonate Environmental Technology Co. Ltd. Shandong Jinan250014 China

ISBN: (纸本)9798350334197

With the increasing shortage of water resources and the improvement of environmental awareness, intelligent water meter monitoring systems have become a hot research topic in the field of water conservation. This paper studies and designs a smart water meter system based on NB-IoT, and discusses its effect in practical applications. This smart water meter monitoring system adopts STM8 microcontroller as the main control chip of the water meter, and adopts the low-power NB-IoT module BC28 module to upload the monitored voltage data, network signal quantity, current water consumption and collection time to the TLink cloud platform in real time, which solves the problems of unstable communication in the working environment, high power consumption of long-term sensor collection and transmission data. At the same time, the water meter can achieve the function of remote control of the water valve switch by driving the stepper motor, which perfectly solves the problems and shortcomings of the current traditional water meter and smart water meter, and greatly meets the development needs of the water industry. © 2023 IEEE.

关键词： Electric power utilization

来源：评论

学校读者我要写书评

暂无评论

Towards next-generation diagnostic pathology:AIempowered label-free multiphoton microscopy

引用

Light(science & Applications) 2024年第12期13卷 2887-2911页

作者： Shu Wang Junlin Pan Xiao Zhang Yueying Li Wenxi Liu Ruolan Lin Xingfu Wang Deyong Kang Zhijun Li Feng Huang Liangyi Chen Jianxin Chen School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Provincial Key Laboratory of Photonics TechnologyFujian Normal UniversityFuzhou 350007China College of Computer and Data Science Fuzhou UniversityFuzhou 350108China Department of Radiology Fujian Medical University Union HospitalFuzhou 350001China Department of Pathology The First Affiliated Hospital of Fujian Medical UniversityFuzhou 350005China Department of Pathology Fujian Medical University Union HospitalFuzhou 350001China New Cornerstone Laboratory State Key Laboratory of Membrane BiologyBeijing Key Laboratory of Cardiometabolic Molecular MedicineInstitute of Molecular MedicineNational Biomedical Imaging CenterSchool of Future TechnologyPeking UniversityBeijing 100091China

Diagnostic pathology,historically dependent on visual scrutiny by experts,is essential for disease *** digital pathology and developments in computer vision technology have led to the application of artificialintelligence(AI)in this *** these advancements,the variability in pathologists’subjective interpretations ofdiagnostic criteria can lead to inconsistent *** meet the need for precision in cancer therapies,there is anincreasing demand for accurate pathological ***,traditional diagnostic pathology is evolvingtowards“next-generation diagnostic pathology”,prioritizing on the development of a multi-dimensional,intelligentdiagnostic *** nonlinear optical effects arising from the interaction of light with biological tissues,multiphoton microscopy(MPM)enables high-resolution label-free imaging of multiple intrinsic components acrossvarious human pathological ***-empowered MPM further improves the accuracy and efficiency of diagnosis,holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic *** review,we systematically outline the applications of MPM in pathological diagnosis across various human diseases,and summarize common multiphoton diagnostic ***,we examine the significant role of AI inenhancing multiphoton pathological diagnosis,including aspects such as image preprocessing,refined differentialdiagnosis,and the prognostication of *** also discuss the challenges and perspectives faced by theintegration of MPM and AI,encompassing equipment,datasets,analytical models,and integration into the existingclinical ***,the review explores the synergy between AI and label-free MPM to forge novel diagnosticframeworks,aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems inclinical settings.

关键词： multiphoton refined diagnosis

来源：评论

学校读者我要写书评

暂无评论

Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

引用

computers, Materials & Continua 2023年第3期74卷 5173-5189页

作者： Hengfu Yang Mingfang Jiang Zhichen Gao School of Computer Science Hunan First Normal UniversityChangsha410205China Hunan Provincial Key Laboratory of Informationization Technology for Basic Education Changsha410205China Department of Applied Mathematics and Statistics College of Engineering and Applied SciencesStony Brook UniversityNY 11794USA

Few previous Reversible Visible Watermarking(RVW)schemes have both good transparency and watermark *** adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding(BTC)compressed domain,called TVB-RVW is proposed in this paper.A new mean image estimation method for BTC-compressed images is first developed with the help of Total ***,a visual perception factor computation model is devised by fusing texture and luminance *** adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC ***,a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark *** visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark *** experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility,and it can achieve a good balance between transparency and watermark visibility.

关键词： Reversible visible watermark block truncation coding visual perception total variation

来源：评论

学校读者我要写书评

暂无评论

3D Reconstruction and Texture Optimization Based on Differentiable Rendering 8

3D Reconstruction and Texture Optimization Based on Differen...

引用

8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Liu, Yongxin Zhao, Haifeng Zhang, Shaojie Fu, Yanping Anhui University Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (纸本)9798350302455

Due to noise and quantization errors inherent in depth cameras, RGB-D based 3D reconstruction algorithms inevitably suffer from defects such as texture blurring and ghosting. However, current texture optimization methods tend to only focus on optimizing one aspect, such as camera pose, geometry, or texture, without considering the highly coupled relationship between them. As a result, it is difficult to achieve global optimality. To address this issue, we propose a joint optimization framework based on differentiable rendering that simultaneously optimizes camera pose, geometry, and texture. By fully exploiting the complementary relationship between these aspects, we are able to reconstruct textures with high fidelity while recovering fine geometric details. First, we propose an optimized geometry model combined with adaptive subdivision, where we selectively subdivide the model only in texture-rich regions to increase the number of vertex facets. Then, we perform geometry optimization to recover high-frequency geometric details evenly in the presence of large geometric errors without incurring computational costs. After the pose correction and geometric model optimization, we use pixel regeneration pipelines to generate clear texture atlases. Comparative evaluations with state-of-the-art texture optimization methods on a public dataset demonstrate the effectiveness of our proposed approach in reducing errors in the reconstruction of 3D models, generating clear textures, and recovering high-frequency geometric details. © 2023 IEEE.

关键词： Textures

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：