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

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A Comprehensive Survey of image Steganography 2

A Comprehensive Survey of Image Steganography

引用

2nd International conference on Sustainable Computing and Smart systems (ICSCSS)

作者： Kalaiarasi, G. Sudharani, B. Jonnalagadda, Sharon Christiana Battula, Harsha Vardhan Sanagala, Bhavana Vignans Fdn Sci Technol & Res Dept ACSE Guntur Andhra Pradesh India

ISBN: (纸本)9798350391558;9798350379990

This research study analyzes the multidimensional landscape of steganography, examining its historical roots, theoretical background, contemporary approaches, and various applications. Beginning with a historical overview, this study investigates the evolution of steganography from its ancient roots to its present iterations in the digital world. Next, the study progresses towards analyzing the fundamental principles and theoretical frameworks that underpin steganographic systems, such as cryptography and digital signal processing. Finally, this study presents a thorough evaluation of contemporary steganographic technologies, which range from simple LSB (Least Significant Bit) substitution techniques to advanced adaptive algorithms and machine learning methods by including deep-learning based steganography and coverless steganography. Notably, this study identifies key challenges, including detection resistance, payload capacity, and robustness against attacks. Overall, this study presents a thorough understanding of steganography, emphasizing its significance as a versatile tool for communication in the digital era, while also highlighting the challenges that pave way for future innovations.

关键词： image steganography Information hiding Convolutional Neural Network Steganography (CNN) Generative Adversarial Network Steganography (GAN) Stochastic computing

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

Security Risk Assessment of Image Classification Model Based...

引用

2023 International conference on Networking and Network Applications, NaNA 2023

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

ISBN: (纸本)9798350327380

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. © 2023 IEEE.

关键词： image classification

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Accelerated Event-Based Feature Detection and Compression for Surveillance Video systems 24

Accelerated Event-Based Feature Detection and Compression fo...

引用

15th ACM Multimedia systems conference (ACM MMSys)

作者： Freeman, Andrew C. Mayer-Patel, Ketan Singh, Montek Univ North Carolina Chapel Hill NC 27515 USA

ISBN: (纸本)9798400704123

The strong temporal consistency of surveillance video enables compelling compression performance with traditional methods, but downstream vision applications operate on decoded image frames with a high data rate. Since it is not straightforward for applications to extract information on temporal redundancy from the compressed video representations, we propose a novel system which conveys temporal redundancy within a sparse decompressed representation. We leverage a video representation framework called AD Delta ER to transcode framed videos to sparse, asynchronous intensity samples. We introduce mechanisms for content adaptation, lossy compression, and asynchronous forms of classical vision algorithms. We evaluate our system on the VIRAT surveillance video dataset, and we show a median 43.7% speed improvement in FAST feature detection compared to OpenCV. We run the same algorithm as OpenCV, but only process pixels that receive new asynchronous events, rather than process every pixel in an image frame. Our work paves the way for upcoming neuromorphic sensors and is amenable to future applications with spiking neural networks.

关键词： event representation event video video processing event vision

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Performance Evaluation of Underwater image Enhancement Techniques

Performance Evaluation of Underwater Image Enhancement Techn...

引用

2024 IEEE International conference on Information Technology, Electronics and Intelligent Communication systems, ICITEICS 2024

作者： Shubhangi, Adagale-Vairagar Gupta, Praveen CSMU Navi Mumbai Mumbai India

ISBN: (纸本)9798350382693

Absorption, scattering, and colour distortion make underwater photography difficult. Marine biology, underwater archaeology, and surveillance need better underwater photos. This research compares cutting-edge underwater image-enhancing methods to assess their efficacy and usefulness. This paper provides a comparative analysis of the various filtering approaches for underwater image enhancement, such as median filtering, average filtering, Gaussian filtering, Wiener filtering, and wavelet-based soft thresholding. The performance of these techniques is evaluated based on the mean square error, peak signal-to-noise ratio, average gradient, PCQI, and UICQI. The effectiveness of the suggested filtering scheme is validated on some sample images of the public UIEB dataset. It provides the analytical finding, advantages, disadvantages and performance of the different techniques for wide variety of underwater images enhancement. The paper also explores underwater image enhancement issues and future approaches. The promising research directions are integrating domain-specific information, real-time processing, and adaptive algorithms for dynamic underwater scenes. The discoveries help increase underwater photography visibility and interpretability, increasing underwater exploration and monitoring systems. © 2024 IEEE.

关键词： Underwater imaging

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2024 18th International conference on Open Source systems and Technologies, ICOSST 2024 - Proceedings

2024 18th International Conference on Open Source Systems an...

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18th International conference on Open Source systems and Technologies, ICOSST 2024

ISBN: (纸本)9798331508692

The proceedings contain 23 papers. The topics discussed include: solar powered auto irrigation monitoring system with plant health indication using image processing;large language model and artificial intelligence based human conversation agent;to enhance graph-based retrieval-augmented generation (RAG) with robust retrieval techniques;automatic timetable generation using neural networks trained by genetic algorithms;assessment of efficient and cost-effective vehicle detection in foggy weather;enhanced detection and prevention of SQL injection and cross-site scripting attacks in web applications: analyzing algorithms and threat modeling approaches;efficient duplicate question detection;and a comprehensive survey on computing services to detect stress and anxiety using smart devices.

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Cloud Architectural Design for image-based Vehicle Positioning in Traffic Management 28

Cloud Architectural Design for Image-based Vehicle Positioni...

引用

28th International conference on System Theory Control and Computing

作者： Beti, Iosif-Alin Herghelegiu, Paul-Corneliu Amarandei, Cristian-Mihai Caruntu, Constantin-Florin Gheorghe Asachi Tech Univ Iasi Dept Automat Control & Appl Informat Iasi Romania Gheorghe Asachi Tech Univ Iasi Dept Comp Sci & Engn Iasi Romania

ISBN: (纸本)9798350364309;9798350364293

Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development of advanced driver assistance systems and autonomous vehicles, relying on precise positioning data for safe navigation. One of the solutions involves using image processing algorithms, which can have two approaches. One approach is decentralized, in which each vehicle performs its own computing steps and determines its position concerning the other nearby vehicles. The second approach, proposed in this paper, is centralized, where each vehicle sends data to a server that uses cloud computing to process all the data in real-time. As such, vehicles can create a more comprehensive view of the driving conditions in the area by using either of these two approaches, which can help them anticipate potential hazards and make more informed decisions.

关键词： computer vision traffic optimization vehicle platooning cloud computing 5G networks vehicle positioning V2V communication

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Optimized Machine Learning for Medical Data Analysis and Disease Prediction

Optimized Machine Learning for Medical Data Analysis and Dis...

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2024 International conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Dubey, Anil Kumar Kapoor, Raman Saraswat, Mala Abes Engineering College Ghaziabad India Bennett University Greater Noida India

ISBN: (纸本)9798350379716

In the context of healthcare and human-computer interaction., this research study provides a thorough analysis of sophisticated computational algorithms for data classification, picture processing, and disease prediction. For multi-disease prediction and intrusion detection, various works have been investigated to arrive at optimal hybrid learning methods and biological feature selection techniques. The role of revolutionary blockchain-based data storage systems and enhanced analysis techniques of EEG data for brain illness detection have been reviewed. Furthermore, an improved bidirectional long short-term memory (LSTM) for time-series data categorization is also discussed. Some noteworthy studies such as the analysis of medical picture defects, application of immersive technology to diagnose Alzheimer's illness and improvements in image resolution and segmentation are also reviewed in this work. Based on the reviewed literature, an improved method is also proposed which is expected to assist with early diagnosis and risk reduction. © 2024 IEEE.

关键词： Brain-Computer Interface Feature Selection Techniques Hybrid Learning algorithms Intrusion Detection systems and Medical image Analysis

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ADIMPR-Net: Automatic Denoising Intra-pulse Multi-parameter Recognition with a Deep Multi-task Network

ADIMPR-Net: Automatic Denoising Intra-pulse Multi-parameter ...

引用

International conference on Electronic Engineering and Information systems (EEISS)

作者： Liu, Yingming Chen, Tao Harbin Engn Univ Coll Informat & Commun Engn Harbin Peoples R China

ISBN: (纸本)9798350351040;9798350351033

To concurrently address the challenges of automatic modulation recognition (AMR) and modulation parameter estimation (MPE) in radar signals, we introduce a multi-task learning (MTL) network architecture designed for intra-pulse multi-parameter recognition through automatic noise reduction. The proposed approach initiates by generating time -frequency image (rn) directly from noisy time-domain signal using a neural network. To effectively capture relevant features from TFls, we employ a VGG-like network Subsequently, the multitask learning framework is utilized to achieve AMR and MPE simultaneously. Four typical intra-pulse modulated signals were simulated in the experiments, simulation results verify the effectiveness and reliability of the proposed algorithms.

关键词： component: Radar signal Signal processing modulation recognition parameter estimation deep learning

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Algorithm for Changing the Size of a Multi-Element Aperture of a Two-dimensional Recursive-Separable Five-Stage Filter for Digital image processing 25

Algorithm for Changing the Size of a Multi-Element Aperture ...

引用

25th IEEE International conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Kamenskiy, Andrey V. Kupriyanova, Kristina S. Podnebesnyy, Andrey V. Kuryachiy, Mikhail I. Borodina, Natalya Tatyana, Akaeva M. Dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (纸本)9798350389234

The paper presents a description of the developed algorithm for changing the size of a multi-element aperture of a recursive-separable five-stage filter for processing digital images generated by specialized optical systems. The developed algorithm has two features: it has the ability to change the size of a multi-element aperture during use;it makes it possible to use the recursive and separable properties. These capabilities make it possible to reduce the processing time of incoming data, which has a positive effect on the efficiency of the optical-electronic imaging system used. The paper presents a block diagram of a two-dimensional recursive-separable five-stage filter, with the help of which an algorithm was developed for changing the size of a multi-element aperture, and a study of the influence of the aperture size on the performance of the developed filter was carried out. As part of the performance evaluation, the developed algorithm was compared with the classical two-dimensional convolution algorithm. Developed algorithm was tested on three test images of different sizes and formats: 1300x700 Bitmap Picture, 1200x1200 Tagged image File, 2900x1900 Joint Photographic Experts Group. During the processing of test images, the dimensions of the multi-element aperture of the developed filter changed. As the aperture size increases, the performance evaluation results also increase. This shows that speeding up the algorithm is an actual task. However, the developed algorithm takes less time than the classical two-dimensional convolution algorithm, from which it can be concluded that the developed solution is effective for both conventional images and images from optoelectronic systems. © 2024 IEEE.

关键词： digital filters digital image processing optical-electronic systems performance real time recursively separable algorithms

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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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