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4th international conference on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning, 3D IT-MSP&DL 2022

4th International Conference on 3D Imaging Technologies- Mul...

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4th international conference on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning, 3D IT-MSP and DL 2022

ISBN: (纸本)9789819911448

The proceedings contain 51 papers. The special focus in this conference is on 3D Imaging Technologies- Multidimensional signal Processing and Deep Learning. The topics include: Research on the Application of 3D Modeling technology in Mechanical Structure Teaching;2D Numerical Model Used to Investigate the Influence of Vegetation on Geomorphological Evolution of Mudflats;design and Experimental Verification of High Functional Density Cubesat System;space Design of Exhibition Hall based on Virtual Reality;Identification of Expressway Traffic States based on the Enhanced FCM Algorithm;algorithms Applied in Soft Tissue Deformation Simulation: A Survey;soft Tissue Cutting based on Position Dynamics;research on Application technology of Multi-source Fusion of 3D Digital Resources in Power Grid;rapid Identification of Herbaceous Biomass based on Raman Spectrum Analysis;a Knowledge Representation Method for Hierarchical Diagnosis Decision-Making Under Uncertain Conditions;research on Spam Detection with a Hybrid Machine Learning Model;research on Weld Defect Object Detection based on Multi-channel Fusion Convolutional Neural Network;Design and Research of Highway Tunnel Construction Positioning System based on UWB;research on Cross Domain Data Analysis and Data Mining technology of Power Grid Digital Benefits;graph Convolutional Neural Networks for Drug Target Affinity Prediction in U-Shaped and Skip-Connection Architectures;SOC Estimation of Lithium Titanate Battery based on Variable Temperature Equivalent Model;research and Implementation of Hybrid Storage Method for Multi-source Heterogeneous Data of Electric Distribution Network;Research on Measuring Method of Ball Indentation based on MATLAB image Edge Detection;multi-feature Extraction of Mineral Zone of Tabling Through Deep Semantic Segmentation.

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Oriented Object Detection in Remote Sensing image based on YOLOV5 14

Oriented Object Detection in Remote Sensing Image Based on Y...

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14th international conference on signal Processing systems, ICSPS 2022

作者： Pan, Dan Wu, Lifang Beijing University of Technology Faculty of Information Technology Beijing China

ISBN: (纸本)9798350336313

In recent years, remote sensing satellites have developed rapidly and accumulated massive high-resolution image data. Using deep learning to solve remote sensing image object detection has become an important research direction. However, due to shooting from a bird's eye view, the object has an oblique Angle. Because of the perspective problem, remote sensing images have boundary problem when the object is near horizontal. When there are a large number of densely tilted object boxes, using horizontal box detection method will cause box occlusion thus missing or mislabeling. Therefore, it is a challenging task to solve remote sensing image object detection. In this paper, we propose the network structure which based on YOLO-V5 and combined with CSL method. Moreover, the loss function is improved to deal with the overlapping problem of tilted object boxes effectively. As revealed by extensive experiments, the average accuracy of this method on DOTA data sets shows a competitive advantage. At the same time, the size of the network is only 16.3m, which is obviously better than the comparison method. © 2022 IEEE.

关键词： Object detection

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Network Intrusion Detection based on Federated Learning with Inherited Private Models 5

Network Intrusion Detection Based on Federated Learning with...

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5th international conference on Video, signal and image Processing, VSIP 2023

作者： Feng, Yanxiang Zhang, Enyan Zhang, Yang Zeng, Zhen Wang, Aili Heilongjiang Province Key Laboratory Of Laser Spectroscopy Technology And Application Harbin University Of Science And Technology Harbin150080 China State Grid Heilongjiang Electric Power Co. Ltd. Harbin Power Supply Company Harbin150010 China The Teaching Department Heilongjiang Open University Harbin150001 China

ISBN: (纸本)9798400709272

To solve the problem of insufficient and imbalanced data in Network Intrusion Detection (NID) in practical scenarios, which leads to low detection accuracy of the model. We propose a network intrusion algorithm based on the Federated Learning with Inheritance Private Model (FedPHP) , which applies Federation Learning (FL) to the field of NID to obtain a well-performing NID model in a privacy-preserving manner in scenarios with unbalanced small samples and multiple participants. This method uses oversampling to preprocess the data, and adds Inheritance Private Model (HPM), knowledge transfer and the matrix Adaptive motion estimation (Adam) algorithm in the training process. The experimental results show that each participant can still get a personalized model with high accuracy and strong robustness under the condition of providing limited data and not infringing the privacy of other parties. The average classification accuracy is 0.9874, and the performance is better than the traditional Deep Learning (DL) and FL network models. © 2023 ACM.

关键词： Learning systems

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Research on Semantic Object Measurement Algorithm based on Object Detection 10th

Research on Semantic Object Measurement Algorithm Based on O...

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10th international conference on Communications, signal Processing, and systems

作者： Wu, Wanqing Ma, Lin Wang, Bin Zhang, Zhongwang Harbin Inst Technol Sch Elect & Informat Engn Harbin 150001 Peoples R China China Natl Aeronaut Radio Elect Res Inst Shanghai 200233 Peoples R China

ISBN: (纸本)9789811903908;9789811903892

As a branch of machine vision, stereo vision has become a research hotspot in recent years. With the development of Augmented Reality (AR), image measurement technology has been proposed. We mainly study the algorithm of using RGB-D image to measure the size of objects in indoor environment, and comprehensively use computer vision technology and image target detection technology to realize the image measurement of objects. Aiming at the problem that there are many kinds of objects in the complex indoor environment and the measurement time in the actual environment, we propose a semantic target measurement algorithm based on target detection. Experimental results show that the target detection network we proposed can effectively identify the object category in indoor environment and measure the size of the recognized semantic target. At the same time. At the same time, the measurement time of the algorithm we proposed is very small, so the measurement efficiency can be improved.

关键词： Indoor Target detection 3D image image measurement

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Analysis of Deep Learning based Secure and Robust System for the Renovation of Medical images on IoMT

Analysis of Deep Learning Based Secure and Robust System for...

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international conference on Computer and Communications Technologies (ICCCT)

作者： Preethi S K. Manoharan Department of Artificial Intelligence and Data Science Sri Sai Ram Engineering College Chennai India Department of Electronics and Communication Engineering SNS College of Technology Coimbatore India

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

Medical healthcare transformations resulted from internet of Medical Things (IoMT) integration because this technology allows physicians to carry out medical imaging examinations promptly and diagnose patient conditions in real time. Medical imaging systems built on the internet of Medical Things framework experience crucial issues that involve weakening of images and privacy risks as well as cyber security threats. This research delivers an extensive investigation about an advanced DL framework which ensures secure medical image restoration inside IoMT platforms. GANs coupled with a Residual Attention Mechanism (RAM) allow the proposed framework to recover medical images that become degraded while retaining essential anatomical elements. A Hybrid Homomorphic Encryption (HHE) scheme brings heightened security through complete confidentiality of data whether it is transmitted or stored. The Adaptive Noise Reduction (ANR) model serves as an integral part to reduce transmission errors and their resulting artifacts and distortions. The model proves its superiority through evaluations on medical imaging benchmarks which yield better Peak signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values compared to contemporary state-of-the-art approaches while users report improved subjective judicial scores (MOS) at the same time. The framework has established its capability for improving image clarity and data security while maintaining patient privacy roles as a promising solution for secure medical image restoration in IoMT platforms.

关键词： Deep learning Surveys Adaptation models PSNR Attention mechanisms internet of Medical Things Real-time systems image restoration Homomorphic encryption Medical diagnostic imaging

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2nd international conference on Mechanical and Energy Technologies , ICMET 2021

2nd International Conference on Mechanical and Energy Techno...

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2nd international conference on Mechanical and Energy Technologies , ICMET 2021

ISBN: (纸本)9789811901072

The proceedings contain 59 papers. The special focus in this conference is on Mechanical and Energy Technologies. The topics include: Role of Artificial Intelligence in Energy and Power Engineering;the Opportunities and Challenges of Implementing Green internet of Things (IoT) Towards Energy Saving Practices in the Current Environment;Influential Effects of Process Parameters of Fused Deposition Modelling on Wear of a PLA Specimen: A Comprehensive Review;review based on Named Entity Recognition for Hindi Language Using Machine Learning Approach;effects of Covid-19 Lockdown: A Perception Survey;Improving Energy Efficiency in Piezoelectric Effect based Synchronous Multicast Protocol (PESM) in Wireless Sensor Networks;a Critical Analysis on the Application of Next-Generation internet of Things (Iot) for Building Efficient Energy systems for Improved Temperature Control and Better Energy Consumption;exploring the Essentials Elements of Data Analysis and Its Impact on Performance Management Framework;role of Data Mining in Detecting Theft and Making Effective Impact on Performance Management;railway Track Monitoring System;an Analytical Approach of Crime Prediction Using Machine Learning;consumer Behaviour on Digital Marketing Platforms—Specifically in Terms of Consumer Loyalty Using Machine Learning;a Review on Various Aerodynamics Control Techniques;the Role of Blockchain technology on Human Rights Management and Business Ethics—Utopia or Dystopia;machine Learning for the Manufacturing of Digital Marketing Techniques and Its Impact on Health Care System;benefits of Digital Education Over the Impact of Pandemic on Indian Higher Education System;decomposition Makes Better Rain Removal: An Enhanced Attention-Guided image De-raining Using Deconvolutions Network;preface.

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Vehicle Black Box Monitoring based ThingSpeak with Long Range technology 2

Vehicle Black Box Monitoring based ThingSpeak with Long Rang...

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2nd international conference on Advances in Engineering Science and technology, AEST 2022

作者： Aramice, Gregor A. Miry, Abbas H. Salman, Tariq M. Mustansiriyah University Department of Electrical Engineering Baghdad Iraq

ISBN: (纸本)9798350334906

Automatic traffic violation fine recording systems play important role to decrease traffic rules violation and accidents, the traffic fine recorded according to traffic violation type and violation location. Manual traffic fine recording may cause false fine recordings. systems developed to guarantee driver rights of such false traffic fines. Vehicle Black Box systems developed for recording variations in vehicles in order to minimize or analyze accidents. Other systems record traffic rules violations automatically and report them to traffic authority system. In this paper, a Vehicle Black Box developed for, safe driving and false traffic fine recordings issues with proofing the availability of a vehicle at traffic violation location with date and time stamps;the system based on internet of Vehicles model with the utilization of Long Range wireless technology to transmit a vehicle acquired data to a base station. Vehicle-to-Infrastructure communication mode designed. Acquired data sent to an internet of Things platform (ThingSpeak) to be stored, visualized and analyzed. Real time test done;Received signal Strength Indicator value measured indicating the performance of LoRa signal propagation at 433MHz modulation in such environment. A correct location obtained and monitored on the ThingSpeak platform. We found that there is no any interference between two vehicles when getting the information from them, where each vehicle has its own code and send its data separately from the other. © 2022 IEEE.

关键词： Vehicles

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Hiding Scheme based on Improved Reduced Difference Expansion in Multi-block Shape 17th

Hiding Scheme based on Improved Reduced Difference Expansion...

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17th international conference on Intelligent Information Hiding and Multimedia signal Processing (IIH-MSP) / 14th international conference on Frontiers of Information technology, Applications and Tools (FITAT)

作者： Lee, Chin-Feng Shen, Jau-Ji Wu, Chin-Yung Chaoyang Univ Technol Dept Informat Management Taichung 41349 Taiwan Natl Chung Hsing Univ Dept Management Informat Syst Taichung Taiwan

ISBN: (纸本)9789811910531;9789811910524

Since the image has the correlation among pixels, the single-layer embedding here uses a block with a shape of 3 x 3. If the reference point that cannot be changed intuitively is located in the center of the block, the image quality or the effect of embedding capacity should be the best situation. This study implements the embedding performance of 9 different scanning patterns proposed by Lee et al. (Data Hiding Using Multi-Pixel Difference Expansion. 2018 3rd international conference on Computer and Communication systems, pp 56-60, 2018) scholars, and the IRDE scheme is calculated with the difference between the block center as the reference point and its eight neighbor pixels to achieve the purpose of hiding data. In addition, according to above, this paper is improved from the method of Lee et al. (Data Hiding Using Multi-Pixel Difference Expansion. 2018 3rd international conference on Computer and Communication systems, pp 56-60, 2018) scholars. based on the malleability of the block shape, we have extended the block shape so that the maximum capacity of each block is increased from the original 8 bits to 35 bits, and at the same time, it can continue to maintain high-quality images by controlling the overflow/underflow mechanism. In order to further explore the relationship between using different block shapes in exchange for high embedding capacity and image quality, this paper designed 5 different shapes and tested them under single-layer. However, the experimental results show that with the continuous increase block shape, the increase of embedding capacity is limited or even tends to be constant. When considering the embedding performance with embedding capacity, the embedding time and the image quality should also be considered. When the shape is 5 x 5, our scheme can achieve greater performance.

关键词： Difference expansion Multi-layer embedding Reversible data hiding

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Perceptual Hashing based on Salient Region and NMF 1

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作者： Wu, Xujun Cui, Chen Wang, Shen Heilongjiang Univ Sch Informat Sci & Technol Harbin Heilongjiang Peoples R China Guangxi Key Lab Cryptog & Informat Secur Guilin Guangxi Peoples R China Jiaxing Univ Coll Math Phys & Informat Engn Jiaxing Zhejiang Peoples R China Harbin Inst Technol Sch Comp Sci & Technol Harbin Heilongjiang Peoples R China

ISBN: (数字)9789811910579

ISBN: (纸本)9789811910579;9789811910562

We propose a novel perceptual hashing based on salient region and a nonnegative matrix factorization (NMF) in this paper. Firstly, the input image is standardized and processed with low-pass filtering. Secondly, the salient region is extracted from the obtained preprocessed image. The minimum bounding rectangle of each salient region is extracted, and the pixels in all rectangles are rearranged to form a secondary image, then the preprocessed image is decomposed by NMF to obtain the coefficient matrix as the final image hash. The algorithm is robust to general content-preserving manipulations through the experiment. The proposed algorithm outflanks some best in the performances of perceptual robustness and discrimination indicated by identification accuracy performances.

关键词： image hashing NMF Salient region

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To Detect Spammer from image-based Spam E-mail through Adjacent-Duplicate Technique

To Detect Spammer from Image-Based Spam E-mail through Adjac...

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2022 IEEE international conference on Knowledge Engineering and Communication systems, ICKES 2022

作者： Patel, Kavita Kumar, Sachin Singh, Vijendra Pratap Singh, Sandeep Kumar Saha, Tapash Kumar Jaiswal, Priya Ashoka Institute of Technology and Management Computer Science and Engineering Department UP Varanasi India Computer Science and Applications Veer Bahadur Singh Purvanchal University UP Jaunpur India Computer Science and Applications Mahatama Gandhi Kashi Vidyapeeth UP Varanasi India Computer Science & Engineering Kashi Institute of Technology UP Varanasi India Computer Science and Applications Kashi Institute of Technology UP Varanasi India

ISBN: (纸本)9781665456371

An Email facility proves to be efficient and more convenient communication way. Now a day, an internet service grows continuously, so information available to user is transformed from text to enriched multimedia. Where, spammer uses a new approach in which text is embedded in images. Widely known image detection algorithm such as optical character recognition (OCR) algorithm is defeated by spam image building techniques where randomization method is used to make sure the entire image is look different to each other. Spam image e-mails are mostly forwarded in a group that have visual similarity but dissimilar due to randomization technique used. The proposed system uses adjacent-duplicate detection technique to identify image-based spam. The system uses conventional spam detection technique to identify image-based spam and then further, use of numerous image-based spam filter to identify all the images which have similarity among them. The system is implemented to gain high identification rate where other side have false positive rate (FPR) is less than 0.001%. © 2022 IEEE.

关键词： Data mining

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