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检索条件"任意字段=International Conference on Signal Image Technology and Internet Based Systems"

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Compression-Encryption based Efficient Dual image Watermarking for e-Healthcare Applications 1

Compression-Encryption Based Efficient Dual Image Watermarki...

引用

1st international conference on Electronics, Communication and signal Processing, ICECSP 2024

作者： Malhotra, Gautam Atri, Abhimanyu Rani, Jyoti Anand, Ashima Thapar Institute of Engineering and Technology Computer Science and Engineering India

ISBN: (纸本)9798350364590

The requirement to protect the authenticity and accuracy of images motivates the implementation of water-marking on these images. Any alteration or interference with medical images might lead to erroneous diagnosis or treatment, as these images are vital for diagnosing and tracking diseases. Moreover, these photographs are regularly transmitted across the internet, increasing the potential for unauthorized access and alteration. Therefore, medical image watermarking is essential to safeguard the reliability and accuracy of these medical images in research and clinical environments. This paper presents a framework of a highly safe and reliable dual watermarking technique that utilizes the NSST-Radon transform to improve medical data security. The ultimate watermarked image is created by incorporating fingerprint and patient information into a medical image, resulting in dual watermarking. After embedding, the final watermarked image is compressed and encrypted to add a security layer. Moreover, our approach uses the best scaling factor to manage the robustness and imperceptibility tradeoffs. The experimental results indicate that the suggested approach demonstrates exceptional overall performance, a high level of imperceptibility, and resilience. The proposed scheme uses dual watermarking to safeguard original medical and non-medical images. The experimental and comparison results show that this strategy produces superior results with remarkable resilience, invisibility, and capacity. © 2024 IEEE.

关键词： Medical imaging

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Wireless Portable Bot Car Controlled by Brain signals 5

Wireless Portable Bot Car Controlled by Brain Signals

引用

5th international conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Kapur, Garima Semwal, Gracy Kushwaha, Pankaj Jaypee Institute of Information Technology Electronics &communication Department Noida India

ISBN: (纸本)9798350379945

This research work presents the implementation of a wireless, portable bot car controlled by brain signals. This pioneering approach integrates advanced neurotechnology with the internet of Things (IoT) and wireless technology. The proposed prototype features effective wireless connectivity, ensuring seamless communication between the brain-computer interface (BCI) and the bot car. Efficient real-time data analysis is achieved through thresholding techniques, enabling rapid and accurate interpretation of brain signals. The incorporation of hysteresis significantly reduces the risk of accidental interruptions caused by unstable sampling, thereby improving the reliability and robustness of the portable bot car. The dynamic interplay of brain signals within this designed framework holds significant potential across multiple industries, including healthcare, assistive technologies, entertainment, and automotive sectors. The user-friendly interface ensures the prototype is accessible and easy to operate, highlighting its practicality and efficiency as an IoT/embedded system-based solution. The project underscores the transformative impact of combining brain signal processing with wireless technology, paving the way for sustainable automotive and healthcare solutions with potential future applications in the field of Brain-Computer Interfaces. © 2024 IEEE.

关键词： Bot (internet)

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based on the improved YOLOv9 laboratory personnel counting system 4

Based on the improved YOLOv9 laboratory personnel counting s...

引用

4th international conference on Digital signal and Computer Communications, DSCC 2024

作者： Liu, Xinyu Ren, Zhengwei Fang, Ming School of Artificial Intelligence Changchun University of Science and Technology Changchun China Zhongshan Institute of Changchun University of Science and Technology Changchun China

ISBN: (纸本)9781510681538

The laboratory, as a research base for university students, is becoming increasingly important to manage. With the development of technology, intelligent laboratory management systems have become a trend. Therefore, how to implement a fast and accurate laboratory management system has become a key issue. To solve these problems, this paper constructs a preliminary laboratory personnel counting system based on the improved YOLOv9 target detection algorithm. The following research work has been done in this paper: The important downsampling part ADown in YOLOv9 is improved, and the convolution module SPD-Conv for low-resolution image detection is combined, which improves the detection effect of YOLOv9 in low-resolution scenes. A laboratory personnel entry and exit counting system is designed. By dividing the entrance line, the statistics of the laboratory entry and exit personnel are achieved. When the number of laboratory personnel returns to 0, an alarm reminder can be given. © 2024 SPIE.

关键词： image enhancement

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An Improved Encoder Network Method for Modulation Recognition 9

An Improved Encoder Network Method for Modulation Recognitio...

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9th international conference on Communication, image and signal Processing, CCISP 2024

作者： Wu, Yunxiao Chang, Jun Li, Dong Li, Meiling School of Information Yunnan University Kunming China

ISBN: (纸本)9798350356656

Automatic modulation recognition (AMR) is a key technology in wireless communication application systems, and the application of deep learning improves the accuracy of AMR. Existing deep learning based modulation recognition methods can only extract local features of the signal, usually by increasing the number of model layers to extract deeper features of the modulated signal, which makes the model complexity enhance the modulation recognition performance degradation. Aiming at this type of problem, an AMR method with TCB (Transformer-Context Broadcasting) model is proposed. The Transformer model is introduced into AMR to extract globally relevant features of the signal, and the unified attention is inserted manually to increase the signal denseness and obtain higher classification accuracy. Experimental results on the dataset show that the TCB model improves the average recognition accuracy by about 4.3%-10.5% compared to existing network models such as CNN2, LSTM, ResNet, CLDNN, etc., which verifies its superiority. © 2024 IEEE.

关键词： signal modulation

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An architecture for confidentiality self-management in the internet of Things 16

An architecture for confidentiality self-management in the I...

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16th international conference on signal-image technology and internet-based systems (SITIS)

作者： Garah, Abdelhamid Mbarek, Nader Kirgizov, Sergey Univ Bourgogne Franche Comte LIB Lab F-21000 Dijon France

ISBN: (纸本)9781665464956

With the growth of the IoT ecosystem, IoT data confidentiality is becoming a critical issue, posing various concerns for customers. Using cryptographic methods to ensure data confidentiality is one of the most common ways for mitigating data confidentiality attacks. Since traditional encryption approaches need important CPU and memory capacity as well as increasing time and energy consumption, researchers have developed a variety of lightweight cryptographic algorithms to provide IoT environments with solutions that take into consideration IoT resources limitations while offering adapted security level. Managing lightweight cryptographic features in an IoT ecosystem is extremely difficult due to the large number of objects, the nature of IoT devices that do not accept the implementation of all possible lightweight solutions, the heterogeneity of the captured data, and the energy required for these lightweight solutions. To address this problem, we propose a novel IoT framework in which lightweight cryptographic features are self-managed according to the Autonomic Computing paradigm in order to ensure IoT data confidentiality while enhancing IoT system performance and extending IoT device lifetime.

关键词： internet of Things IoT data confidentiality Autonomic Computing Self-management IoT architecture

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Hyperspectral image anomaly detection based on minimum noise fraction and tensor low-rank theory 4

Hyperspectral image anomaly detection based on minimum noise...

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4th international conference on Green Communication, Network, and internet of Things, CNIoT 2024

作者： Zhang, Pengyuan Lin, Qing Du, Binhua Wu, Yaochen Sun, Lei School of Systems Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9781510685710

Hyperspectral imaging (HSI) provides a powerful guarantee for the accurate identification of various targets due to its rich spectral and spatial information. Anomaly detection, a significant application of HSI, is inevitably affected by noise during the imaging process. To achieve effective HSI anomaly detection in complex environments, this paper propose minimum noise fraction (MNF) and tensor low-rank anomaly detection by replacing principal component analysis (PCA) in PCA-tensor low-rank and sparse representation (TLRSR) with MNF as a preprocessing step. Experimental tests using real hyperspectral data demonstrate that the proposed method can effectively reduce noise in HSIs and significantly enhance the anomaly detection accuracy. © 2024 SPIE.

关键词： signal to noise ratio Detection and tracking algorithms Principal component analysis Covariance matrices Hyperspectral imaging Target detection Interference (communication) Data modeling Denoising Sensors

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image Processing based on Inter-frame Color Feature Matching for Visible Light Positioning 2

Image Processing Based on Inter-frame Color Feature Matching...

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2nd international conference on signal Processing and Intelligent Computing, SPIC 2024

作者： Yu, Baozhu Liu, Xiangyu Chen, Yaoheng Guo, Lei Bao, Jianbo Sun, Jiandong Shenyang Ligong University School of Information Science and Engineering Shenyang China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China Chongqing University of Posts and Telecommunications School of Communication and Information Engineering Chongqing China Nari Group Corporation State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350368888

The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the high complexity of traditional image processing algorithms, existing VLP systems are unable to provide real-time positioning services. In response to the above issue, we propose an image processing mechanism based on the inter-frame color feature matching method, which includes the equidistant sampling processing, low complexity decoding algorithm, and color feature matching-based LED region of interest (ROI) determination method. The results show that the system average positioning delay is 80.2ms, indicating better system real-time performance. © 2024 IEEE.

关键词： Color image processing

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Research on Real-Time Data Transmission and signal Processing System of CIM Practical Training Teaching Platform based on 5G Network 2

Research on Real-Time Data Transmission and Signal Processin...

引用

2nd IEEE international conference on image Processing and Computer Applications, ICIPCA 2024

作者： Cheng, Xuemei Zhang, Hao Shandong University of Engineering and Vocational Technology Jinan250000 China Poly Shandong Real Estate Group Corporation Limited Jinan250000 China

ISBN: (纸本)9798350360240

In order to solve the problems of 'digital signal processing', such as many common knowledge points, difficult teaching, difficult visual teaching, and so on, a software platform for 'signal processing' open teaching is built based on Visual C++6.0. This system is to cooperate with the teaching content of CIM, but also to improve the practical ability of students, so that they can more easily and quickly understand some of the more complex digital signal theory. The timing of the beam position signal is optimized based on the existing down sampling method, and the digital AGC and slow application signal processing modules are completed. We need to get turn-by-turn, quick application, and track closing data simultaneously. The experiment shows that the system can obtain the multi-frequency position information including the actual running state well. The advantages of this system are easy to control parameters, easy to use, and strong expansibility. This project plans to further improve the system in the future research work so as to achieve better teaching and practical application purposes. © 2024 IEEE.

关键词： 5G mobile communication systems

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A stochastic nonmonotone trust-region training algorithm for image classification 16

A stochastic nonmonotone trust-region training algorithm for...

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16th international conference on signal-image technology and internet-based systems (SITIS)

作者： Yousefi, Mahsa Calomardo, Angeles Martinez Univ Trieste Dept Math & Geosci Trieste Italy

ISBN: (纸本)9781665464956

In this work, we consider the target of solving the nonlinear and nonconvex optimization problems arising in the training of deep neural networks. To this aim we propose a nonmonotone trust-region (NTR) approach in a stochastic setting under inexact function and gradient approximations. We use the limited memory SR1 (L-SR1) updates as Hessian approximations when the curvature information is obtained by several different strategies. We provide results showing the performance of the proposed optimizer in the training of residual networks for image classification. Our results show that the proposed algorithm provides comparable or better testing accuracy than standard stochastic trust-region depending on the adopted curvature computing strategy and outperforms the well-known Adam optimizer.

关键词： nonlinear optimization stochastic quasi-Newton methods SR1 deep neural networks nonmonotone trust-region

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5th international Symposium on signal and image Processing, ISSIP 2024

5th International Symposium on Signal and Image Processing, ...

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5th international Symposium on signal and image Processing, ISSIP 2024

ISBN: (纸本)9789819795147

The proceedings contain 31 papers. The special focus in this conference is on signal and image Processing. The topics include: A Blockchain-based Secure Framework for Storage and Access of Surveillance Video Data;encountering the Challenges and Awareness of internet Security;Data-Driven Strategies for Twitter Engagement: Hashtag Recommendations and API Insights;Analyzing and Visualizing AI Decision-Making for Human-Centered Interaction and Trust;AI-ML-based Handover Techniques in Next-Generation Wireless Networks;castle Defender: Design and Implementation of Game based on Pygame;optimizing Healthcare: Enhancing Disease Management with Recommendation systems;optimizing Diabetes Prediction Models for Enhanced Health Data Processing;comparative Analysis of Classification Models Using Various Feature Sets;An Early Detection of Tomato Plant Disease with Deep Reinforcement Learning and CNN;ioT-Powered Health Monitoring System for Protecting Vital Organs Through Cloud-based Diagnosis;LASKV: Lightweight Authenticated Session Key Agreement for Video Surveillance System;Data Analyses of Factors Influencing Sustainable Adoption of Online Public Services: An Extended UTAUT Analysis in North Macedonia;a Comprehensive Review on Real-Time Campus Compass;deep Learning Approaches for Early Detection of Bovine Respiratory Diseases in Cattle;identifying Suitable Cloud Storage Services from Cross Cloud Platforms based on the Requirements;storage-Savvy Frame Recorder: Enhancing Storage Efficiency and Inspection Speed*;lossless Medical image Compression Using Block-Wise Burrows–Wheeler Transform and Modified Run Length Encoding;advancing Software Defect Detection and Prevention: Bridging Gaps in Early-Stage and Evolving Software systems;a New Way to Communicate: Deep Learning for Deaf and Dumb People;dependent Binomial: A Family of Distributions Derivable by Modifying a Base.

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