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QAAD: Quality Aware Adaptive Denoising 11

QAAD: Quality Aware Adaptive Denoising

引用

11th ieee international conference on signal Processing and Integrated Networks, SPIN 2024

作者： Parse, Tejas Ajay Awasthi, Tanishq Yadav, Dushyant Joshi, Piyush Indian Institute of Information Technology Department of Computer Science Sri City Chittoor India

ISBN: (纸本)9798350308433

image denoising is a fundamental task in computer vision and image processing, crucial for improving the visual quality and interpretability of images captured in noisy environments. In this research, we propose a quality-Aware adaptive denoising (QAAD) approach that leverages the Blind/Referenceless image Spatial Quality Evaluator (BRISQUE) as a key factor in determining the optimal denoising algorithm for an image. Our methodology involves an initial assessment of image quality using BRISQUE scores for a diverse set of images. Subsequently, we employ various image quality enhancement algorithms to enhance the image quality. Through extensive experimentation, we assess the performance of these enhancement algorithms with respect to specific ranges of BRISQUE scores. This evaluation enables us to determine which denoising algorithm performs optimally for images falling within particular BRISQUE score ranges. The innovation in our approach lies in its adaptability. When an image proceeds for denoising, its BRISQUE score is calculated and, based on this score, the most suitable denoising algorithm for that specific image is selected. This adaptive strategy ensures that the chosen denoising algorithm is tailored to the inherent noise characteristics of the input image, leading to superior denoising results. Our experimental results demonstrate the effectiveness of our approach in enhancing image quality and achieving state-of-The-Art denoising results. This research contributes to the field of image processing by providing a data-driven and adaptive solution for image denoising, ultimately enhancing the quality of images in diverse real-world applications. © 2024 ieee.

关键词： image denoising

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Design of capacitor feedback amplifier for amplifying ECG signal using a folded-cascode amplifier 6

Design of capacitor feedback amplifier for amplifying ECG si...

引用

2023 ieee 6th international conference on Information systems and Computer Aided Education, ICISCAE 2023

作者： Zhou, Zhiyu Southwest Jiaotong University School of Information Science and Technology Chengdu China

ISBN: (纸本)9798350313444

In recent times, propelled by the swift evolution of the internet industry, the realm of intelligent healthcare has undergone significant advancements. The portable ECG monitoring system has emerged as a prominent research area within the medical field. This technology addresses the complexities associated with conventional medical ECG monitoring equipment and the detection process, enabling real-time monitoring and assessment of cardiac activity. The article delves into the critical realm of amplifying ECG signals with significant implications for medical applications. Specifically, the paper outlines a design involving the implementation of a capacitive feedback amplifier, which is constructed using a folded-cascode amplifier configuration. The whole design is simulated by using CMOS 180nm technology. The differential gain of this circuit is 43.94dB, which can effectively amplify the ECG signal. The CMRR is 80.53dB. Aimed at decreasing power consumption, the design's power consumption is 10.8uW. Also, the passband frequency is 2.95Hz to 7.85kHz. This work provides a comprehensive exploration of the amplifier's architecture and its potential utilization in medical settings, ultimately contributing to improved diagnostics and patient care as well as highlighting its potential to advance the field of healthcare technology. © 2023 ieee.

关键词： capacitive feedback amplifier ECG folded-cascode amplifier healthcare low-power

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UAV image Denoising based on Swin Deformer for Power System Condition Monitoring 8

UAV Image Denoising based on Swin Deformer for Power System ...

引用

8th international conference on Intelligent Computing and signal Processing, ICSP 2023

作者： Wang, Dong Ye, Linwei Xi'an Jiaotong-Liverpool University Department of Mechanics and Robotics Systems Suzhou China Xi'an Jiaotong-Liverpool University Department of Information Management and Information System Suzhou China

ISBN: (纸本)9798350302455

In order to improve the quality of UAV transmission line inspection pictures and ensure the effectiveness of the defect recognition network, this paper proposes a model based on Swin Deformer to denoise the pictures. The data set of this method is the original data set collected by UAV, and the test set and training set are obtained by classifying the raw data. At the same time, Gaussian noise is added to generate tags to ensure the effect of supervised learning. Finally, the test set is input into the pre-training model, and the results obtained prove that our noise reduction network can greatly improve the image quality and further improve the effect of line maintenance. © 2023 ieee.

关键词： image enhancement

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Optimizing Key-Selection for Face-based One-Time Biometrics via Morphing

Optimizing Key-Selection for Face-based One-Time Biometrics ...

引用

ieee international Workshop on Information Forensics and Security (WIFS)

作者： Osorio-Roig, Daie Ghafourian, Mahdi Rathgeb, Christian Vera-Rodriguez, Ruben Busch, Christoph Fierrez, Julian Hsch Darmstadt Biometr & Internet Secur Res Grp Darmstadt Germany Univ Autonoma Madrid UAM Biometr & Data Pattern Analyt BiDA Lab Madrid Spain

ISBN: (纸本)9798350324914

Nowadays, facial recognition systems are still vulnerable to adversarial attacks. These attacks vary from simple perturbations of the input image to modifying the parameters of the recognition model to impersonate an authorised subject. So-called privacy-enhancing facial recognition systems have been mostly developed to provide protection of stored biometric reference data, i.e. templates. In the literature, privacy-enhancing facial recognition approaches have focused solely on conventional security threats at the template level, ignoring the growing concern related to adversarial attacks. Up to now, few works have provided mechanisms to protect face recognition against adversarial attacks while maintaining high security at the template level. In this paper, we propose different key selection strategies to improve the security of a competitive cancelable scheme operating at the signal level. Experimental results show that certain strategies based on signal-level key selection can lead to complete blocking of the adversarial attack based on an iterative optimization for the most secure threshold, while for the most practical threshold, the attack success chance can be decreased to approximately 5.0%.

关键词： adversarial attack iterative optimization face recognition privacy protection security cancelable biometrics

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Optimizing Loss Functions in Conditional GANs for Astronomical image Deconvolution: A Comparative Study at Varied Epochs

Optimizing Loss Functions in Conditional GANs for Astronomic...

引用

2024 ieee international conference on signal Processing, Informatics, Communication and Energy systems, SPICES 2024

作者： Vasudev, Vishnu Rajesh, M.V. APJ Abdul Kalam Technological University Electronics and Communication Engineering College of Engineering Chengannur Kerala India College of Engineering Poonjar Electronics and Communication Engineering Kerala India

ISBN: (纸本)9798350376135

This study explores the optimization of loss functions in conditional Generative Adversarial Networks (cGANs), specifically the pix2pix model, for the deconvolution of astronomical images obtained from the Hubble Space Telescope. The objective is to mitigate the effects of atmospheric distortion, commonly referred to as the "seeing"effect. We systematically evaluated various combinations of Mean Absolute Error (MAE), Mean Squared Error (MSE), Structural Similarity Index (SSIM), and Binary Cross-Entropy (BCE) with logits as loss functions for the generator. These were tested at different training epochs-10, 20, 30, 40, and 50. Our results indicate that a specific weighting of BCE with logits, MAE, and SSIM-1, 1, and 50, respectively-significantly enhances the performance, yielding higher Peak signal-To-Noise Ratio (PSNR) and SSIM values post 30 epochs. In addition, we compared our cGAN-based method with conventional techniques, including Wiener deconvolution, Richardson-Lucy algorithm, and Total Variation (TV) deconvolution. Our proposed method demonstrated superior clarity and detail retention. © 2024 ieee.

关键词： signal to noise ratio

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Blind Spots of Objective Measures: Exploiting Imperceivable Errors for Immersive Tactile internet 13

Blind Spots of Objective Measures: Exploiting Imperceivable ...

引用

13th ACM/ieee international conference on Cyber-Physical systems (ICCPS )

作者： Kroep, H. J. C. Gokhale, V Prasad, R. Venkatesha Delft Univ Technol Delft Netherlands

ISBN: (纸本)9781665409674

Tactile internet (TI) enables the transfer of human skills over the internet, enabling teleoperation with force feedback. Advancements are being made rapidly at several fronts to realize a functional TI soon. Generally, TI is expected to faithfully reproduce operator's actions at the other end, where a robotic arm emulates it while providing force feedback to the operator. Performance of TI is usually characterized using objective metrics such as network delay, packet losses, and RMSE. Pari passu, subjective evaluations are used as additional validation, and performance evaluation itself is not primarily based on user experience. Hence objective evaluation, which generally minimizes error (signal mismatch), is oblivious to subjective experience. In this paper, we argue that user-centric designs of TI solutions are necessary. We first consider a few common TI errors and examine their perceivability. The idea is to reduce the impact of perceivable errors and exploit the imperceivable errors to our advantage, while the objective metrics may indicate that the errors are high. To harness the imperceivable errors, we design Adaptive Offset Framework (AOF) to improve the TI signal reconstruction under realistic network settings. We use AOF to highlight the contradictory inferences drawn by objective and subjective evaluations while realizing that subjective evaluations are closer to ground truth. This strongly suggests the existence of `blind spots of objective measures'. Further, we show that AOF significantly improves the user grade, up to 3 points (on a scale of 10) compared to the standard reconstruction method.

关键词： Tactile internet user experience QoS teleoperation

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Whole Body Bone Scan image Enhancement Algorithm based on Laplacian and Adaptive Wiener Filter 5

Whole Body Bone Scan Image Enhancement Algorithm Based on La...

引用

5th international Academic Exchange conference on Science and technology Innovation, IAECST 2023

作者： Zhang, Qingbiao He, Gang Southwest University of Science and Technology School of Computer Science and Technology Mianyang China

ISBN: (纸本)9798350357738

Whole body bone imaging is a commonly used method for the diagnosis of bone metastases, but the images acquired by this method have some problems such as low resolution and poor contrast. In this paper, we propose an image enhancement algorithm for whole-body bone imaging based on Laplacian and adaptive Wiener filtering. To enhance the image's contrast, we employ the Laplacian operator as a primary tool. The image is then processed by adaptive Wiener filtering to remove the noise amplified by the enhancement of the Laplacian operator. Experiments show that compared with the traditional Wiener filtering algorithm and the Laplacian operator, the proposed algorithm has better visual effect, and the enhanced image has higher peak signal-to-noise ratio. The results indicate that this approach effectively enhances image contrast while minimizing noise, which is conducive to the detection of lesions and reduce the problems of misdiagnosis, missed diagnosis and poor positioning. © 2023 ieee.

关键词： image enhancement

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A Comprehensive Review Analysis of image Similarity Detection Techniques in Deep Learning to Detect the image Plagiarism

A Comprehensive Review Analysis of Image Similarity Detectio...

引用

2024 international conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Naudiyal, Anjali Singh, Vineeta Rastogi, Ritesh Joshi, Kapil Kumar, Amit School of Applied and Life Sciences Uttaranchal University Premnagar Dehradun India Chhatrapati Shahu Ji Maharaj University Department of Computer Science and Engineering Kalyanpur Uttar Pradesh U.P. Kanpur208024 India Noida Institute of Engineering and Technology Department of Computer Science Greater Noida India Uttaranchal University Department of Computer Science & Engineering Premnagar Dehradun India Graphic Era deemed to be university Dehradun India

ISBN: (纸本)9798350379716

The proliferation of images on the internet in the era of artificial intelligence has increased the risk of image plagiarism. image plagiarism is the most serious problem in the field of research. Using artificial intelligence (AI) tools, writers and scholars now modify text, codes, and images. While these artificial intelligence systems have certain advantages, the writers gain more in the research domain. Machine learning includes deep learning, while artificial intelligence includes machine learning. The majority of Deep Learning's attention is directed towards images with several characteristics. Deep learning uses a variety of techniques to process images. Once image plagiarism has been found in a document with the help of plagiarism detection tools, it should be eliminated. In order to make the internet of Things more environmentally friendly, plagiarism must also be found and eliminated. Finding plagiarism in the source code is also a difficult task. In the presented paper, various methods of similarity detection are discussed and compared in order to determine which method of image similarity detection is most effective in detecting plagiarism in images or in the text of images. If the similarity index between the images is lower, then there is a greater likelihood of plagiarism. Different types of distances are calculated in order to check the image similarity. These methods are also used to check the similarity index with their accuracy. Anyone is able to select the most accurate and user-friendly Deep Learning method for image similarity with ease after going over all of the available ways for detecting image plagiarism. © 2024 ieee.

关键词： Contrastive Learning

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DC Terminal Impedance Modeling and Stability Analysis for VSG-Controlled Grid-Connected Inverter

DC Terminal Impedance Modeling and Stability Analysis for VS...

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2024 ieee international conference on DC Technologies and systems, DCTS 2024

作者： Su, Xinyang Wang, Minghao Xue, Ying Chen, Junyu Shi, Wenzhuo Xu, Zhao The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong The University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China South China University of Technology School of Electric Power Engineering Guangzhou China

ISBN: (纸本)9798350379464

As a kind of grid-forming control method that can effectively provide virtual inertia for the power grid, the virtual synchronous generator (VSG) control has received increasing attention in recent years. However, the VSG control will extract energy from the DC side during a grid frequency drop, which brings a burden on the stability of the DC side of a VSG. To address this problem, this paper establishes a fully analytical small-signal model of the VSG DC terminal impedance, incorporating both the inertia mechanism and the DC side dynamics. The accuracy of the model is validated through comparison with the sweep frequency results of the simulation. Finally, the Nyquist criterion is employed to analyze the DC stability of the VSG, and the simulation results match well with the theoretical predictions. © 2024 ieee.

关键词： Synchronous generators

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Feature Extraction based Domain Kickout Method for Fractal image Compression 1

Feature Extraction Based Domain Kickout Method for Fractal I...

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1st ieee international conference on Innovations in High Speed Communication and signal Processing, IHCSP 2023

作者： Bhardwaj, Sucheta Chaurasia, Vijayshri Ahmad Siddiqui, Ebtasam Patel, Vivek Sharma, Abhishek Tiwari, Manish Firmware Engineer Motherson Innovation Germany Maulana Azad National Institute of Technology Department of Electronics & Communication Engineering Bhopal India Oriental Institute of Science & Technology Department of Electronics & Communication Engineering Bhopal India Schneider Electric Electronics Hardware Principal Technical Expert France

ISBN: (纸本)9798350345957

In fractal image compression, similarities between the picture's self-similar components, often known as fractals, are exploited in order to create a novel method of image representation. In order to depict these fractals, it makes use of affine transformations. The significant amount of time needed for the encoding process is this method's most significant drawback. In this paper, we propose a fast fractal image compression system. This system works by reducing the effective number of domain images by using feature extraction, which in turn reduces the computational overheads and ultimately results in a reduction in the amount of time it takes to encode the image. © 2023 ieee.

关键词： Fractals

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