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Enhanced Steganographic Scheme based on Difference Expansion in Digital images 8

Enhanced Steganographic Scheme Based on Difference Expansion...

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8th international conference on Information technology, Information systems and Electrical Engineering, ICITISEE 2024

作者： Wahono, Dimas De La Croix, Ntivuguruzwa Jean Ahmad, Tohari Teknologi Sepuluh Nopember Department of Informatics Institut Surabaya Indonesia University of Rwanda Kigali Rwanda

ISBN: (纸本)9798350368970

The advancement of technology in transmitting information over public networks has underscored the importance of data security to protect information. Various research studies have introduced numerous data protection approaches, such as steganography, to enhance the security of confidential information transmitted over public networks. Steganography in digital images, which was a focal point for sensitive data protectors using digital media, has not been sufficiently effective in safeguarding sensitive data due to remarkable distortions found in the stego images. To address this shortcoming, this article introduces a new steganographic approach utilizing pixel difference expansion within small blocks of a digital image. The proposed method segments the cover image into blocks of four pixels calculates differences between these pixels, and embeds secret data by modifying pixel values when the differences fall within a specific range. This process is recorded in a secret key table for accurate data extraction. Experimentations performed on grayscale images of size 512 × 512, got from a publicly used steganography dataset, show a Peak signal-to-Noise Ratio (PSNR) value ranging between 58.451 and 79.298 decibels (dB), which is always superior to the 30 dB, a standard minimum threshold value for quality stego images in all cases. © 2024 IEEE.

关键词： Pixels

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Fall Detection Technique for Older Individuals based on Deep Layered Neural Networks Embedded with Transfer Learning 5

Fall Detection Technique for Older Individuals based on Deep...

引用

5th international conference on Smart systems and Inventive technology, ICSSIT 2023

作者： Deepika, J. Akilandeswari, J. Sona College of Technology Department of Information Technology India

ISBN: (纸本)9781665474672

The vital priority of the society is to render helping hand to most fragile category of people such as older individuals, neurogenerative disease affected patients, etc. to lead their normal routine social life being physically active without lowering their quality of life and not losing their autonomy. As ageing progress, the elderly adults experience falls and those consequences lead to lesser quality of life due to the injuries occurred L This further adds to the fear of falling and reduced physical activity. The first solution of protection against the negative effects of falling is to identify fragility and high fall risk at an early stage. The development of novel techniques to identify potential fallers before any fall occurs would be the second solution of protection. The Artificial lntelligence (AD technique is used to examine and prevent falls from the signal-hised image gathered from the gyroscope or the accelerometer sensor information. The several layers of convolutional neural network are used with different dilation rates for extracting different categories of feature selection. The performance evaluation hised on the experimental results on the signal image dataset proves higher accuracy of classification rate. © 2023 IEEE.

关键词： Convolutional neural networks

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Underwater image Restoration based on An Improved Underwater image Formation Model 14

Underwater Image Restoration Based on An Improved Underwater...

引用

14th IEEE international conference on Wireless Communications and signal Processing (WCSP)

作者： Fan, XinNan Zhou, Xuan Shi, PengFei Sun, HuanRu Ye, ShuYue Hohai Univ Coll Internet Things Engn Changzhou Peoples R China

ISBN: (纸本)9781665450850

Underwater images often show characteristics of low contrast, low visibility and color distortion. To improve underwater image quality, a novel underwater image restoration algorithm is proposed in this paper. First of all, we put forward an underwater image restoration network (UIRnet) based on CNN(Convolutional Neural Network) for transmission estimation in the underwater imaging model. Besides, the Leaky ReLU(Rectified Linear Units) activation function and SENet(Squeeze-and-Excitation Networks) unit are used to improve the ability of extracting image features and training parameters. Secondly, the fuzzy patch dataset which is used as input dataset is synthesized by the underwater optical imaging model and randomly generated transmission. Meanwhile, the corresponding transmission value is used as label dataset. Then, we use the dataset to train and optimize all parameters in the UIRnet. Finally, the trained UIRnet is used in underwater image restoration. The experimental results show that the proposed algorithm can restore the details of the image, improve the contrast, and have a more natural visual effect.

关键词： image restoration image formation model Underwater images

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Electrical Fault Detection based On Infrared Temperature Measurement technology 12

Electrical Fault Detection Based On Infrared Temperature Mea...

引用

12th IEEE international conference on Communication systems and Network Technologies, CSNT 2023

作者： Wang, Jing Zhang, Xinglei State Grid Jibei Electric Power Co. Ltd. Beijing Ehv Power Transmission Company Beijing China

ISBN: (纸本)9781665462617

This paper mainly analyzes the infrared temperature measurement equipment of power system. Its hardware architecture mainly includes three parts: monitoring front-end, wireless communication network and monitoring center. The monitoring front-end hardware is installed with a main control module, which is successively linked with image acquisition, image compression module and infrared alarm module;An infrared thermal imager is linked to the image acquisition;The monitoring center is also equipped with a computer host server and an infrared camera display device. In this paper, the distribution of high temperature of transmission line is detected online by infrared thermal image, and the security status of transmission line is judged through the online measurement technology of transmission line infrared thermal image, and the early warning signal of high temperature thermal anomaly is accurately provided. In order to effectively protect the safety of existing transmission line from high temperature thermal overshoot, it plays a great role. © 2023 IEEE.

关键词： Electric lines

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Intelligent Pedestrian Crossing System at Urban Intersection based on Machine Vision Intelligent Recognition System 2

Intelligent Pedestrian Crossing System at Urban Intersection...

引用

2nd IEEE international conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Cheng, Huiting Chongqing Vocational College of Transportation School of Rail Transportation Chongqing China

ISBN: (纸本)9798350317558

Urban intersections are important places where pedestrians and vehicles meet, and pedestrian crossing safety has become a key issue. An intelligent pedestrian crossing system based on a machine vision intelligent recognition system is proposed as a solution to improve pedestrian traffic safety and street crossing experience. This study uses a machine vision algorithm model, combined with image and video processing technology, to design and implement an intelligent pedestrian crossing system at an urban intersection. Experimental testing and performance evaluation of the system were conducted, focusing on key indicators such as pedestrian detection and recognition accuracy, signal light status recognition accuracy, and system response time. Experimental results show that the pedestrian detection and recognition accuracy of this system is between 88% and 95%. The pedestrian intelligent crossing system shows high accuracy in pedestrian detection and recognition accuracy, and can accurately calibrate the position of pedestrians and Identify their identity information. The system also shows a high accuracy in the signal light status identification task and can accurately determine the current signal light status. In addition, the system has a short reaction time and can take necessary actions and decisions in time to ensure pedestrians cross the street safely. © 2024 IEEE.

关键词： Intelligent Identification System Intelligent Pedestrian Crossing System Machine Vision Right-of-Way Allocation

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EAFLoc: A Few-shot Fingerprint Localization Approach with Environmental Awareness

EAFLoc: A Few-shot Fingerprint Localization Approach with En...

引用

2023 international conference on Intelligent Communication and Networking, ICN 2023

作者： Liao, Minghao Zhu, Zelin TongJi University Department of Computer Science and Technology Shanghai China

ISBN: (纸本)9798350357677

Localization technology is the foundation of location-based services, which plays a crucial role in various fields such as mobile communication and the internet of Things(IoT). Various approaches have been proposed to achieve precise localization, such as GNSS-based, Time-based, Angle-based, and Proximity-based approaches. However, there are specific drawbacks, including strict time synchronization requirement, susceptibility to signal reflections, and high demands on infrastructure. As a supplement, RSSI-based and image-based localization approaches have been extensively researched and utilized in recent years. Nevertheless, these approaches are often limited by labor-intensive annotations and researches on utilizing RSSI and image modalities to achieve high-precision localization are also limited. Additionally, there are few researches on localization under few-shot and zero-shot conditions. Therefore, in this paper, we propose EAFLoc, an environment-aware few-shot multimodal fingerprint localization approach. EAFLoc addresses the challenge of efficient modality information fusion. Also, data augmentation algorithms are designed for few-shot scenarios, and we further explore localization under zero-shot scenarios with channel prediction methods. Finally, the superiority and effectiveness of EAFLoc are validated on a real dataset. The experimental results demonstrate that EAFLoc achieves better performance compared to the traditional approaches. © 2023 IEEE.

关键词： Location based services

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Embedded-based Touch Screen Driver Design and Implementation

Embedded-Based Touch Screen Driver Design and Implementation

引用

2023 IEEE international conference on image Processing and Computer Applications, ICIPCA 2023

作者： Gu, Wen Liang, Zhichao Sun, Weijian City Institute Dalian University of Technology Dalian China

ISBN: (纸本)9798350314670

With the development of the internet, embedded systems have become one of the hottest industries at present, and the embedded market still shows a huge demand. People have put forward higher requirements for embedded products, such as stable, intuitive, convenient and easy to operate. Touch screen undoubtedly provides people with great convenience, so in embedded systems, touch screen design with good performance, stable operation and high precision has positive and extensive significance. At the same time, in the embedded field, the Linux operating system's open source code licensing model, easy to customize, easy to cut and port features, making Linux the most popular and most popular operating system in the embedded development platform and application platform. Embedded systems are superior in terms of high specialisation and real-time, with a wide range of application-centric and computer technology-based applications. As today's electronic devices continue to be intelligent, the traditional keyboard, mouse and other human-computer interaction has been unable to meet the needs of people, people want more convenient human-computer interaction tools. The touch screen through the finger touch can achieve the operation of positioning, greatly simplifies the input method of electronic equipment, truly zero distance operation, so the touch screen has been more and more widely used. This paper is based on the Samsung S3C2410 embedded, design and implementation of the touch screen program, to achieve the control and operation of the touch screen, with touch screen sensitivity, positioning touch screen position and other characteristics, to improve the use of touch screen efficiency and user experience. Finally, the feasibility and effectiveness of the design program is verified through experiments. © 2023 IEEE.

关键词： Real time systems

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Automated Brain Abnormality Segmentation using Modified JAYA algorithm based Fuzzy C-Means Clustering 1

Automated Brain Abnormality Segmentation using Modified JAYA...

引用

1st international conference on Software, systems and Information technology, SSITCON 2024

作者： Jeenath Shafana, N. Priya Lakshmi, S. Vijayalakshmi Ramani, U. Ramaraj, Kottaimalai Thilagaraj, M. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India Cmr Institute of Technology Department of Computer Science and Engineering Bengaluru India K Ramakrishnan College of Engineering Department of Electrical and Electronics Engineering Tiruchirappalli India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Krishnankoil India Mvj College of Engineering Department of Industrial Internet of Things Bengaluru India

ISBN: (纸本)9798350352931

The main risk factors in humans, irrespective of gender or location, are anomalies of the brain, such as tumors and strokes. In healthcare facilities, the degree of disability and underlying cause of brain lesions are typically evaluated by means of regular methods created by trained clinicians. During this procedure, signals and images of the brain are collected in a controlled setting. Selecting an appropriate separation method is essential to getting the desired results. The novel JAYA algorithm, which relies on meta-heuristics, aids in the reclustering of the FCM segmentation results in our suggested techniques, yielding more productive delineation results with clear borders with 86% of Dice Score. However, the exploitation and exploration techniques for searching become more flexible and help identify the optimal solution faster by adjusting the desired function with respect to the accommodating cluster location and population size. Regarding the processing speed, optimal exploitation, and exploratory abilities, the suggested strategy outperforms the other available metaheuristic optimization techniques. © 2024 IEEE.

关键词： image segmentation

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An Optimized Graph Neural Network-based Approach for Intrusion Detection in Smart Vehicles 6th

An Optimized Graph Neural Network-Based Approach for Intrus...

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6th IFIP international conference on internet of Things, IFIP IoT 2023

作者： Zambare, Pallavi Liu, Ying Texas Tech University Lubbock United States

ISBN: (纸本)9783031458774

Due to recent developments in vehicle networks (VNs), more and more people want their electric cars to have access to sophisticated networking features and perform a variety of advanced activities. Several technologies are installed in these autonomous vehicles to aid the drivers. Cars have unquestionably become smarter as we’ve been able to install more and more gadgets and applications on them. As a result, the security of assistant and self-drive systems in automobiles becomes a life-threatening concern, since hostile attacks that cause traffic accidents may infiltrate smart cars. This research provides a technique based on the Graph Neural Network (GNN) deep learning (DL) model for detecting intrusions in VNs. This model can recognize attack patterns and classify threats accordingly. Experimentation utilizes car-hacking datasets. These files include DoS attacks, fuzzy attacks, driving gear spoofing, and RPM gauge spoofing. The car-hacking dataset is converted into image files, and the GNN model provided works with the newly produced image dataset. The findings of comparing our model to DL models indicate that our GNN model is superior. In specific, the test case scenarios may identify abnormalities with respect to detection F1-score, recall, precision, and accuracy to ensure accurate detection and identification of potential false alarm concerns. © 2024, IFIP international Federation for Information Processing.

关键词： internet of things

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Lightweight Deep-Learning based Music Genre Classification: A Study

Lightweight Deep-Learning Based Music Genre Classification: ...

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2023 international conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Rama, A. Mythili, N. Rajakumar, M.P. Arunmozhi, S. Mohammed, Mazin Abed Rajinikanth, V. Saveetha School of Engineering Simats Department of CSE TN Chennai602105 India St. Joseph's Institute of Technology Department of Computer Science and Engineering TN Chennai600119 India St. Joseph's College of Engineering Department of Artificial Intelligence and Data Science TN Chennai600119 India Manakula Vinayagar Institute of Technology Department of Electronics and Communication Engineering TN Puducherry605 107 India College of Computer Science and Information Technology University of Anbar Department of Artificial Intelligence Anbar31001 Iraq Saveetha School of Engineering Simats Division of Research and Innovation Department of CSE TN Chennai602105 India

ISBN: (纸本)9798350315127

Deep-learning (DL) applications that are used real-time across various industries have gained a lot of traction and have become increasingly popular, especially when it comes to data-driven recommendation systems. This work aims to develop a DL scheme to support the music-recommendation system (MS) based on the music data. The various phases of this scheme includes;(i) data collection and signal-image conversion to get the necessary RGB scale images from the data, (ii) pre-trained DL based feature extraction, and (iii) deep-features based detection to recommend the appropriate music. This research considered the classic- (CL) and pop-music (PO) for the examination and the achieved results are evaluated to substantiate the performance of this arrangement. In this work, the signal-image conversion procedure is implemented to convert 1D signal to 2D image and then it is examined using proposed technique. The experimental outcome is separately presented for (i) spectrogram and (ii) synchro-extracting-transform and obtained results are presented. The experimental investigation is presented with MobileNet variants and this study authorizes that the implemented scheme achieved a better detection MobileNetV2 (>99%) compared to other schemes in this study. © 2023 IEEE.

关键词： Real time systems

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