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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16443 条记录，以下是1251-1260 订阅

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Design of English Teaching Resource System Based on Deep Learning

Design of English Teaching Resource System Based on Deep Lea...

引用

image processing and Computer Applications (ICIPCA), IEEE International conference on

作者： xiaojun Jiang School of Translation Studies Xi'an Fanyi University Xi'an Shaanxi China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

This paper seeks to design an English deep learning-based online teaching assistant system in this paper. The basic structure of the system is described in a web environment, which is composed of a system login module and a homework function module. It is then designed that the examinations and examination information management module reinforce its role as an online English teaching instrument. Training in deep learning networks is on the software side of system to improve quality of English online teaching resources. The results of the experiment show that training efficiency and login success rate both are higher than that in traditional systems. OK, then this system's application performance is good.

关键词： Training Deep learning Distance learning Multimedia systems Instruments image processing Computer applications Software Information management

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Security Risk Assessment of image Classification Model Based on ANP-TOPSIS

Security Risk Assessment of Image Classification Model Based...

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International conference on Networking and Network Applications (NaNA)

作者： Zhiheng Zhang Zeyu Liu Li Yang Tingbo Zhe Jian Wu School of Computer Science and Technology Xidian University Xi'an China Guiyang Aviation Motor Co. Ltd Guizhou China

Recently, machine learning algorithms have been widely used in the fields of image processing, network security and natural language processing, etc., profoundly affecting human life. However, machine learning algorithms have the characteristics of uncertain output, vulnerability to adversarial attacks, and unexplained decision-making processes, which seriously threaten the security of machine learning-based face recognition, Malware detection, and autonomous driving. Hence, it is imperative for the security practitioners to evaluate algorithm security to ensure that security needs are met. In this article, the authors propose a set of security assessment index systems and methods for machine learning algorithms for image classification scenarios: Refer to the security specification of machine learning algorithms and requirements to construct the security index system of image classification model. Furthermore, The Analytic Network Process(ANP) is applied to quantify the index weights and the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) is applied to screen the optimal model, and finally the sensitivity analysis is applied to prove the stability of the proposed method. Experimental results show that this method has certain value and effect in assessing the security and model screening of image classification models.

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Compact Fuzzy BLS Driven Semi-Supervised Multi-Objective Evolutionary Adaptive Multiple-Kernel Fuzzy Clustering for Color image Segmentation 4

Compact Fuzzy BLS Driven Semi-Supervised Multi-Objective Evo...

引用

4th International conference on Natural Language processing, ICNLP 2022

作者： Zhao, Feng Liu, Yu Xi'an China

ISBN: (数字)9781665495448

ISBN: (纸本)9781665495448

Multi-objective evolutionary algorithms (MOEAs)-based fuzzy clustering have been successfully applied to image segmentation problems. However, these MOEAs require a lot of expensive fitness function evaluations. In order to make full use of image prior information and multi-kernel advantages as well as further improve the segmentation performance and time efficiency for image segmentation, a compact fuzzy broad learning system (CFBLS) surrogate-assisted semi-supervised multi-objective evolutionary adaptive multiple-kernel fuzzy clustering (CFBLS-S2AMKFC) algorithm is proposed in this paper. The main contributions of CFBLS-S22AMKFC are described as follows: first, a semi-supervised adaptive multiple-kernel weights fuzzy clustering fitness function is constructed to obtain satisfactory segmentation results;second, using CFBLS model predict the real objective function values in the MOEAS framework, thus reducing the time complexity of the algorithm, and third, constructing a semi-supervised multi-kernel clustering validity index to select the optimal solution from the final nondominated solution set. Experiment results on Berkeley images demonstrate that the proposed algorithm CFBLS-S2AMKFC has good segmentation accuracy and low time cost. © 2022 IEEE.

关键词： Multiobjective optimization

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Contour Extraction of Surgical Stoma Surfaces Using 2.5D images from Smartphone 3D Scanning 26

Contour Extraction of Surgical Stoma Surfaces Using 2.5D Ima...

引用

26th IEEE Signal processing: algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Monroy, Francisco Luquin Hussein, Rania University of Washington Electrical and Computer Engineering Department Seattle United States

ISBN: (纸本)9798350304985

In this paper, we present a technique for extracting stoma outlines from 2.5D images acquired through smartphone-based 3D scanning. Accurate stoma outlining plays a crucial role in tailoring ostomy wafers, thereby minimizing stoma damage, preserving the health of surrounding skin, and ultimately enhancing the health-related quality of life for stoma patients. Our proposed method leverages a widely used contour algorithm and incorporates error analysis to assess its effectiveness and precision. Through a series of experiments, we investigate the potential and limitations of smartphone 3D scanning in achieving precise and personalized stoma contouring. Additionally, we introduce an error metric to evaluate the performance of the technique quantitatively. Our findings shed light on the possibilities for advancements in 3D scanning technology and image processing techniques, marking a significant step towards harnessing smartphone technology for improved ostomy management and patient care. © 2023 Division of Signal processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： image segmentation

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Research on Computer image Recognition Technology Based on Artificial Intelligence

Research on Computer Image Recognition Technology Based on A...

引用

International conference on systems and Informatics (ICSAI)

作者： Jing Li Yuxi Liu Yahong Ma Feng Liu School of Electronic Information Xijing University Xian China

ISBN: (数字)9798331510138

ISBN: (纸本)9798331510145

In order to solve the problem of fast processing for ultra-high-resolution images in embedded systems, this paper proposes a multi-mode tracking and recognition method based on embedded processing architecture, through the construction of a multi-GPU hardware processing system, the large-scale image parallel processing algorithm is studied, and a variety of image processing modes such as full-frame, full-window tracking and tracking scanning are designed, and experimental verification is carried out on ultra-high-resolution images. The multi-GPU architecture and large-scale image parallel processing algorithm described in this paper have certain advantages over traditional processing methods.

关键词： image recognition Software design image resolution Software algorithms Computer architecture Switches Parallel processing Hardware Artificial intelligence Informatics

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Communicate and Control System for Planar Single-Axis Photovoltaic Array Clusters in Complex Terrain

Communicate and Control System for Planar Single-Axis Photov...

引用

IEEE International conference on Signal processing, Communications and Computing (ICSPCC)

作者： Yue Zhao Wenxuan Yang Yun Wang Luoxiao Yang School of Automation and Information Engineering Xi'an University of Technology Xi'an Shaanxi China School of Marine Science and Technology Northwestern Polytechnical University Xi'an Shaanxi China

ISBN: (数字)9798350366556

ISBN: (纸本)9798350366563

In the current discourse on renewable energy, photovoltaic (PV) technology surfaces as a keystone in the sustainable energy portfolio. However, the efficiency of PV systems is often compromised by geographical and temporal challenges, specifically in undulating terrains where shadowing can markedly degrade output. Addressing this, we introduce the Dynamic Adaptive Posture Adjustment Control for Photovoltaic Cluster systems (DAPAC-PVCS), a novel system engineered to dynamically modulate the orientation of PV panels in real-time. Through an adept fusion of hardware innovation and evolutionary computation algorithms, DAPAC-PVCS transcends traditional fixed installations by counteracting shadowing effects and optimizing energy capture. Computational analyses authenticate that this avant-garde control system significantly surmounts the efficiency benchmarks of extant models, heralding a 1.5 % amplification in annual power generation. Our contribution marks a quantum leap in PV technology, poised to enhance the viability of solar farms in topographically complex regions and bolster the shift towards renewable energy paradigms.

关键词： Photovoltaic systems Wireless communication Renewable energy sources Technological innovation Signal processing algorithms Evolutionary computation Control systems Real-time systems Computational efficiency Shadow mapping

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Hole repair of 3D terrain mesh in satellite stereo image reconstruction

Hole repair of 3D terrain mesh in satellite stereo image rec...

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2024 International conference on Remote Sensing, Mapping, and Geographic Information systems, RSMG 2024

作者： Bao, Qiwei Liu, Jun Liu, xining Zhao, Limin Yuan, Zhanliang Chen, xingfeng Li, Jiaguo Li, Huafu Zhang, Haixiang School of Surveying and Land Information Engineering Henan Polytechnic University Jiaozuo454003 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Sanya Institute of South China Sea Geology Guangzhou Marine Geological Survey China Geological Survey Sanya572024 China

ISBN: (纸本)9781510685826

When constructing a 3D surface grid using point cloud data closely matched with high-resolution satellite stereo images, holes often appear due to matching failures or limitations of triangulation algorithms, affecting the grid's integrity and the accuracy of subsequent applications. To solve this problem, a boundary contraction algorithm is studied for repairing mesh holes. The research focuses on different terrain conditions such as mountains, plains, and cities, and evaluates the effectiveness of boundary contraction algorithms in repairing holes. Using visual inspection methods, the quality of the repaired mesh is checked to ensure its integrity, smoothness, continuity, and topological correctness. The experimental results of GF-7 satellite images show that the boundary contraction algorithm can effectively fill holes in various terrain environments, significantly improving the geometric quality and overall integrity of the mesh, verifying its feasibility as a reliable mesh repair method, and providing strong support and verification for the application of the boundary contraction algorithm in actual terrain data processing. © 2024 SPIE.

关键词： Mesh generation

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A Machine Learning Framework for Skin Cancer Detection using Transfer Learning

A Machine Learning Framework for Skin Cancer Detection using...

引用

International image processing, Applications and systems conference (IPAS)

作者： Mary Linda Panakal Augustine Sotirios Spanogianopoulos Mhd Saeed Sharif Department of Computer Science and Digital Technologies School of Architecture Computing and Engineering University of East London London UK School of Electrical and Mechanical Engineering University of Portsmouth Portsmouth UK

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

This paper uses deep learning algorithms including InceptionV2, InceptionV3, DenseNet, MobileNet, and VGG19 to improve skin cancer detection. This research aims to improve skin cancer diagnosis. This work aims to determine the most effective evolutionary metrics-based technique to recognizing skin cancer, which is comparable to other diseases. Ultimately, our paper aims to create a realistic skin cancer detection system that uses the best deep learning algorithm. This discovery might improve medical diagnostics, leading to earlier diagnosis and improved healthcare outcomes.

关键词： Deep learning Machine learning algorithms image processing Transfer learning Medical diagnosis Reliability Skin cancer image classification

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Alzheimer's level classification by 3D PMNet using PET/MRI multi-modal images

Alzheimer's level classification by 3D PMNet using PET/MRI m...

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IEEE International conference on Electrical Engineering, Big Data and algorithms (EEBDA)

作者： Li, Chao Song, Liyao Zhu, Guangpu Hu, Bingliang Liu, Xuebin Wang, Quan Chinese Acad Sci Xian Inst Opt & Precis Mech XIOPM Key Lab Spectral Imaging Technol Xian Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Xian Inst Opt & Precis Mech Key Lab Biomed Spect Xian Xian Peoples R China Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian Peoples R China

ISBN: (纸本)9781665416061

The accurate diagnosis of Alzheimer's disease (AD) has an important impact on early treatment. Positron emission tomography (PET) and magnetic resonance imaging (MRI) are popular imaging methods and are used to facilitate the identification and evaluation of AD. In this paper, we proposed a VGG-style 3D convolutional neural network (3D CNN) model, which is named 3D PET-MRI Net (3D PMNet), and it uses DiffGrad optimizer to speed up the convergence of the model and Focalloss function to improve the classification performance of unbalanced data processing. The multi-modal feature information of 3D MRI and PET images can be extracted using the 3D PMNet model, which provides convenience for AD diagnosis. Tenfold cross-validation was performed on the data of each patient in the data set to determine the group classification. The results showed that the proposed method achieves 97.49%, 81.25%, and 76.67% accuracy in the classification tasks of AD: NC, AD: MCI, and NC: MCI, respectively. Our PMNet reached 72.55% accuracy in AD: NC: MCI three group classification, which is significantly better than the other reported network models.

关键词： Alzheimer's disease 3D CNN Multi-modality image classification PET/MRI

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Quality of Service-based Multi-Task Scheduling for Cooperative Multi-radar systems 12

Quality of Service-based Multi-Task Scheduling for Cooperati...

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12th IEEE International conference on Control, Automation and Information Sciences, ICCAIS 2023

作者： Zhang, Zishi Yuan, Ye Yi, Wei Yan, Junkun University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Xidian University National Key Laboratory of Radar Signal Processing Xi'an China

ISBN: (纸本)9798350328783

In this paper, an algorithm based on quality of service (QoS) framework is proposed to address the multitask scheduling problem in complex collaborative multi-radar scenarios. The task scheduling problem is described as an NP-hard mixed integer optimization problem in terms of task quality and task efficiency. To efficiently tackle the characteristic of the optimization problem, we proposed a two-step decoupling algorithm based on convex relaxation focusing on optimizing overall performance. Then, two comparison algorithms are proposed in this paper to benchmark against the proposed task scheduling algorithm. By contrasting these algorithms with the proposed approach, the study assesses the effectiveness and superiority of the new method in optimizing task utility and addressing the challenges of multi-task scheduling in multi-radar cooperative surveillance scenarios. © 2023 IEEE.

关键词： Quality of service

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