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3rd IEEE International Conference on Recent Advances in Systems Science and engineering, RASSE 2023

作者： Jayasankar, Sreelakshmi Brindha, T. Noorul Islam Centre for Higher Education Department of Computer Science and Engineering Tamil Nadu India Noorul Islam Centre for Higher Education Department of Information Technology Tamil Nadu India

ISBN: (纸本)9798350341676

The human skin serves as the exterior protective layer of body, shielding the interior organs beneath from damaging UV rays, dust, and pollution. Cancer is one of the main causes of mortality worldwide as per WHO. One-Third of all malignancies that have been diagnosed around the world are skin cancers. Skin cancer has been more common during the last few decades. Melanoma and its global incidence rate have been quickly increasing in recent years. Identifying skin cancer in its early stages can result in a considerable drop in the fatality rate. Melanoma's complicated nature and structure make it difficult to distinguish unique aspects based on the type, shape of the cancer cells, color and texture. This literature review gives an overview of the present state of melanoma detection methods. The review discusses the numerous approaches and procedures used to diagnose melanoma, as well as their potential accuracy, limitations in accuracy, and prospects for improvement. It will concentrate on various ways of diagnosis, such as imaging techniques such as dermoscopy and various methods in artificial intelligence. The review will also look at the problems and potential breakthroughs in the field of melanoma detection. © 2023 IEEE.

关键词： Cancer cells

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Multiscale Convolutional Relation Network for Hyperspectral Image Classification with Small Samples 9

Multiscale Convolutional Relation Network for Hyperspectral ...

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

作者： Lu, Xinhua Hao, Jiaxuan Wang, Hua Huang, Junbo School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou450066 China School of Information Engineering Nanyang Institute of Technology Nanyang473000 China School of International Education Hebei University of Technology Tianjin300130 China

ISBN: (纸本)9798350376548

Achieving high classification accuracy under a limited number of training samples remains a key challenge in hyperspectral image (HSI) classification. Relation network can effectively improve the performance of HSI classification under small samples conditions by learning and measuring the relationships between samples. However, relation network often cannot fully extract and utilize feature information from HSI. To improve feature extraction capability, we propose a multiscale convolutional relation network. This network includes a dual branch multiscale CNN aiming at comprehensively capturing features across various kernel sizes. And it incorporates a multihead attention fusion module for fusing multiscale features, thereby facilitating the learning of multilevel contextual semantic information. We also design a novel metric module for relation network, which improves ability to extract deep features and fully utilizes spatial information to establish relationships between feature maps and categories effectively. Experiments have shown that the proposed method can achieve more competitive results. © 2024 IEEE.

关键词： Convolutional neural networks

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MLPDR: High Performance ML Algorithms for the Prediction of Diabetes Retinopathy

MLPDR: High Performance ML Algorithms for the Prediction of ...

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2023 IEEE International Conference on Network, Multimedia and information technology, NMITCON 2023

作者： Madhuri G, Sindhu Chokkanathan, K. Mahesh, T.R. Musthafa, M.Mohamed Vanitha, K. Vivek, V. Manipal Institute of Technology Department of Information Technology Bengaluru India Manipal Academy of Higher Education Manipal India Madanapalle Institute of Technology & Science Department of Ai Madanapalle India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India Tamil Nadu Erode India Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350300826

In today's world, millions of imaging analyses are performed every week, and medical imaging plays a significant role in that. It is a process of creating visual representation based on the functioning of human organs or tissues to identify abnormalities or study diseases. Diabetes has been regarded as one of the most prevalent diseases by many researchers. Blindness or other retinal alterations based on the eye's vision, such as difficulty reading or seeing distant things, may occur, which has an impact on diabetes in humans. A new computer aided diagnosis system based on image processing of retinal images can be analyzed in order to detect diabetic patients in advance. In this study, the eye retina based on image processing techniques is analyzed and machine learning techniques have been used to extract features of eye and several computational intelligence Machine Learning techniques like Support Vector Machines (SVM) and Principal Component Analysis (PCA). These Computational Intelligence techniques have been used to detect the diabetic in advance. Several performance metrics have been considered such as Root Mean Square Error (RMSE), Peak Signal Noise Ratio (PSNR), Entropy (E), and Accuracy (A) in obtaining the better accuracy results for detection of diabetic retinopathy in early stages. The experimental results show that, SVM outperforms with an accuracy of 95%. © 2023 IEEE.

关键词： Principal component analysis

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Target tracking method of Siamese networks based on the broad learning system

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CAAI Transactions on Intelligence technology 2023年第3期8卷 1043-1057页

作者： Dan Zhang C.L.Philip Chen Tieshan Li Yi Zuo Nguyen Quang Duy Navigation College Dalian Maritime UniversityDalianChina Innovation and Entrepreneurship Education College Dalian Minzu UniversityDalianChina Computer Science and Engineering College South China University of TechnologyGuangzhouChina Department of Computer and Information Science Faculty of Science and TechnologyUniversity of MacaoMacaoChina School of Automation Engineering University of Electronic Science and Technology of ChinaChengduChina Faculty of Navigation Vietnam Maritime UniversityHaiphongVietnam

Target tracking has a wide range of applications in intelligent transportation,real‐time monitoring,human‐computer interaction and other ***,in the tracking process,the target is prone to deformation,occlusion,loss,scale variation,background clutter,illumination variation,etc.,which bring great challenges to realize accurate and real‐time *** based on Siamese networks promotes the application of deep learning in the field of target tracking,ensuring both accuracy and real‐time ***,due to its offline training,it is difficult to deal with the fast motion,serious occlusion,loss and deformation of the target during ***,it is very helpful to improve the performance of the Siamese networks by learning new features of the target quickly and updating the target position in time *** broad learning system(BLS)has a simple network structure,high learning efficiency,and strong feature learning *** at the problems of Siamese networks and the characteristics of BLS,a target tracking method based on BLS is *** method combines offline training with fast online learning of new features,which not only adopts the powerful feature representation ability of deep learning,but also skillfully uses the BLS for re‐learning and re‐*** broad re‐learning information is used for re‐detection when the target tracking appears serious occlusion and so on,so as to change the selection of the Siamese networks search area,solve the problem that the search range cannot meet the fast motion of the target,and improve the *** results show that the proposed method achieves good results on three challenging datasets and improves the performance of the basic algorithm in difficult scenarios.

关键词： broad learning system siamese network target tracking

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A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection

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computer Systems Science & engineering 2022年第6期41卷 1043-1056页

作者： Xiaorui Zhang Wenfang Zhang Wei Sun Xingming Sun Sunil Kumar Jha Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszowVoivodeship100031Poland

In a telemedicine diagnosis system,the emergence of 3D imaging enables doctors to make clearer judgments,and its accuracy also directly affects doctors’diagnosis of the *** order to ensure the safe transmission and storage of medical data,a 3D medical watermarking algorithm based on wavelet transform is proposed in this *** proposed algorithm employs the principal component analysis(PCA)transform to reduce the data dimension,which can minimize the error between the extracted components and the original data in the mean square ***,this algorithm helps to create a bacterial foraging model based on particle swarm optimization(BF-PSO),by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding,thereby achieving the optimal balance between embedding capacity and imperceptibility.A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.

关键词： 3-D medical watermarking robust watermarking PCA BF-PSO

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The Performance Analysis of Distributed Denial of Service Attacks in Wireless Networks 2

The Performance Analysis of Distributed Denial of Service At...

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Agrawal, Trapty Raghavendra, R. Singh, K. Ranjith Rajiv Gandhi, N. Dhabliya, Dharmesh Katariya, Jitendra Kumar Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Information Technology Karnataka Bangalore India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Civil Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350308846

Complete studies paper that examines the outcomes that malicious 0.33-celebration actors will have on Wi-Fi networks via dispensed denial of carrier (DDoS) attacks. This paper explores the available numerous assault models and the potential countermeasures that may be applied if you want to mitigate the damage due to such assaults. In addition, this paper focuses on the capability blessings related to deploying preventative measures to lessen the impact of such assaults. Moreover, the paper investigates existing attack trends. It affords an outline of the safety techniques to be had for limiting the harm caused by DDoS attacks in wireless networks. By comparing and analyzing the performance of diverse protection mechanisms, this paper offers an evidenceprimarily based evaluation of the effectiveness of DDoS attack safety answers. ultimately, this paper concludes with the aid of supplying recommended measures for strengthening and ensuring the safety of Wi-Fi networks against malicious actors. © 2023 IEEE.

关键词： Evaluation Measures Performance Recommended Strengthening

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Image Fusion Using Wavelet Transformation and XGboost Algorithm

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computers, Materials & Continua 2024年第4期79卷 801-817页

作者： Shahid Naseem Tariq Mahmood Amjad Rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba Department of Information Sciences Division of S&TUniversity of EducationLahore54770Pakistan Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Sciences University of EducationVehari CampusVehari61100Pakistan Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Mathematical Sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Recently,there have been several uses for digital image *** fusion has become a prominent application in the domain of imaging *** create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same *** fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual *** fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on *** research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet *** fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient *** precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain *** tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is *** use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter *** simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original *** study enhances the performance of the eXtreme Gradient Boosting(XGBoos

关键词： Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain

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Knowledge Graph for China's Genealogy1

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IEEE Transactions on Knowledge and Data engineering 2023年第1期35卷 634-646页

作者： Wu, Xindong Jiang, Tingting Zhu, Yi Bu, Chenyang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Anhui Hefei230009 China Hefei University of Technology Research Institute of Big Knowledge Anhui Hefei230009 China Mininglamp Technology Mininglamp Academy of Sciences Beijing100102 China Hefei University of Technology School of Computer Science and Information Engineering Anhui Hefei230009 China Hefei University of Technology Ministry of Education Key Laboratory of Knowledge Engineering with Big Data Anhui Hefei230009 China

Genealogical knowledge graphs depict the relationships of family networks and the development of family histories. They can help researchers to analyze and understand genealogical data, search for genealogical descendant paths, and explore the origins of a family. However, the heterogenous, autonomous, complex, and evolving natures of genealogical data bring challenges to the development of contemporary genealogical knowledge graph models. Applying existing methods to genealogical data may be improper because general knowledge graph models lack in-depth domain knowledge. In this paper, we propose a genealogical knowledge graph model named Huapu-KG that combines HAO intelligence (human intelligence + artificial intelligence + organizational intelligence) to implement the construction and applications of genealogical knowledge graphs. Furthermore, challenges in constructing genealogical knowledge graphs are demonstrated, and experiments conducted on real-world genealogical datasets verify the feasibility and effectiveness of our proposed model. © 1989-2012 IEEE.

关键词： History

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A DC Microgrid Attack Detection Strategy based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise

A DC Microgrid Attack Detection Strategy based on Complete E...

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2023 International Conference on Smart Electrical Grid and Renewable Energy, SEGRE 2023

作者： Wen, Mengfei Wen, Yian Zhang, Yu Zhang, Zhongke Zhu, Ren Changsha Preschool Education College School of Information Technology Changsha China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha China Central South University School of Computer Science and Engineering Changsha China Changsha Preschool Education College School of Preeducation Changsha China

ISBN: (纸本)9798350323269

With the continuous development of renewable energy technologies and intelligent control systems, DC microgrids have become a popular direction for the development of future energy systems with the advantages of high efficiency and flexibility. However, because DC microgrids are closely connected to the Internet, their complex network structures and communication protocols make them easy targets for cyber attacks. Therefore, this paper proposes an attack detection strategy based on the complete ensemble empirical mode decomposition with adaptive noise for detecting abnormal output data in DC microgrids. First, the voltage signal with a fast response rate is analyzed based on the effect of data injection on the output of DC microgrids. Secondly, sufficient feature extraction is performed on the output voltage using complete set empirical mode decomposition. Then, calculate the energy of the decomposed feature mode function, and set an anomaly threshold detection scheme based on the energy interval during normal operation of the DC microgrid to complete the detection of the abnormal output of the DC microgrid. Finally, the simulation verifies the reliability and effectiveness of the proposed detection strategy. © 2023 IEEE.

关键词： Renewable energy resources

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Performance Boosting of Automatic Sun Following Panels Using Soft Computing Technique 6

Performance Boosting of Automatic Sun Following Panels Using...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Goswami, Shubhashis Kumar, Kaushal Kumar, Santosh Anandhasilambarasan, D. Kannimuthu, S. Kolekar, V.K. School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India School of Engineering & Technology K. R. Mangalam University Department of Mechanical Engineering Gurugram India Invertis University Department of Computer Applications Bareilly India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India Karpagam College of Engineering Department of Information Technology Coimbatore India Vishwakarma Institute of Information Technology Computer Engineering Pune India

ISBN: (纸本)9798350304480

The optimizing for the sun committee's tilt position using soft computation is subject of research study. At particular inclination angles above a flat surface, distinct radiation types provide various amounts of exposure. Properly set, the degree of tilt additionally delivers greater electricity using the exact same screen. A research on optimizing the slant inclination was done. Initially a significant power improvement was made by using genetic codes to continuously modify the slant angle. Sunny tracking is crucial to improving overall gadget performance for many solar-powered generators, concentrators, and rectangular plates. Mechanism honor, a key component of process functioning, is basic scientific method to modeling the procedure that is controlled either to identify plant undiscovered characteristics. An Automated network based on artificial intelligence is presented in order to define and simulate a dual axis sunlight tracking system. Both alongside and despite the application of scaled variables, a clear proportionate integral then a liquid-based logical control mechanism was investigated and integrated within the photovoltaic function. © 2023 IEEE.

关键词： Angle Azimuth Artificial Neural Network Fuzzy logic (FL) Genetic Algorithm (GA) Latitude Passive Actuator Photovoltaic Panel Solar Energy Solar Tracking System

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