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

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Machine Learning for signal Processing in Communication systems

Machine Learning for Signal Processing in Communication Syst...

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2024 international conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Reddy, PoliLokeshwara Shreyas, Chanda Bhargavi, Pamulapati. Raja, G.V. Rani, D. Leela Maheswari, S. Anurag University Department of Electronics and Communication Engineering Telangana Hyderabad500088 India Kkr & Ksr Institute of Technology and Sciences Department of Computer Science Engineering Andhra Pradesh Guntur522017 India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Karnataka Bengaluru562106 India Mohan Babu University Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Kongu Engineering College Department of Electrical and Electronic Engineering Tamil Nadu Perundurai638060 India

ISBN: (纸本)9798331543617

The traditional styles of signal processing are passing constraints in their capability to handle the different and dynamic character of ultramodern data transfers. This is because communication systems are getting increasingly complicated. The operation of machine literacy presents a potentially useful answer since it enables data-driven, adaptive approaches that have the eventuality to ameliorate signal processing performance. This composition provides a comprehensive examination of a variety of machine literacy ways and their operations in important disciplines such as modulation recognition, noise reduction, channel estimation, and signal discovery. The study demonstrates how machine literacy ways may vastly increase the effectiveness, delicacy, and robustness of signal-processing tasks in communication systems. This is fulfilled through detailed analysis and comparison. With the help of machine literacy, unborn communication systems will be suitable to attain advanced situations of robotization and intelligence, which will pave the way for further developments in areas similar to wireless dispatches, the internet of Effects(IoT), and other areas. In light of these findings, it's clear that machine literacy can fully transfigure assiduity by furnishing new shoes and approaches to the optimization of signal processing in the unborn generation of communication networks. © 2024 ieee.

关键词： Noise abatement

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Tag-Aware Weakly-Supervised Online Hashing with Enhanced Joint Representation

Tag-Aware Weakly-Supervised Online Hashing with Enhanced Joi...

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2025 ieee international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Wang, Na Zhan, Yu-Wei Chen, Zhen-Duo Wang, Yongxin Luo, Xin Xu, Xin-Shun School of Software Shandong University Jinan China Department of Computer Science and Technology Tsinghua University Beijing China School of Computer Science and Technology Shandong Jianzhu University Jinan China

ISBN: (纸本)9798350368741

Weakly-supervised online hashing has garnered significant attention recently, yet several challenges remain unresolved, such as how to effectively denoise tags, and how to efficiently learn hash functions in dynamic online scenarios. To tackle these challenges, we propose a novel method named Tag-Aware Weakly-supervised Online Hashing with enhanced joint representation (TA-WOH). Our method creates an enhanced joint representation with CLIP-based features in order to reduce the tag noise. Additionally, we introduce a tag association and noise model for improved similarity matrix and hash code learning. A novel mapping mechanism is developed to align joint representations with the optimal tag space, enhancing both the accuracy and robustness of the model. The computational complexity of TA-WOH is dependent solely on the size of the incoming data, ensuring scalability and efficiency for large-scale datasets. Extensive experiments on two datasets demonstrate that our method surpasses several state-of-the-art methods in both accuracy and efficiency. © 2025 ieee.

关键词： Learning to Hash Online Hashing Social image Retrieval

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The Art System of Picture Composition based on Computer Video Processing technology 2

The Art System of Picture Composition Based on Computer Vide...

引用

2nd ieee international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Qiu, Shan Wang, Ning Zibo Technician College Shandong China

ISBN: (纸本)9798350347456

With the development of science and technology and the renewal of media means in the era of cultural industry, electronic media develops rapidly, video image technology with digital realization as the carrier develops rapidly, and gradually becomes an independent art form, which indicates the arrival of a new type of art. The purpose of this paper is to study the picture composition art system based on computer video processing technology. From the picture composition art overview to the introduction of basic knowledge of computer science, and then to the main technology of computer video processing, summed up the coordinate space and its transformation, geometric transformation technology of graphics and other knowledge. This paper mainly analyzes the program flow of picture composition art system and modern geometric composition law module, and introduces the application of video frame in image processing. The real-time performance and effect of the system are tested. When processing video art image composition, the CPU usage of real-time processing is about 40%, If you don't process the video, but just play it, the average CPU usage is about 20%. The real-time performance of video processing can be realized effectively through the image synthesis art system. © 2023 ieee.

关键词： Video signal processing

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Deployment of Proposed EfficientNeXt on NXP *** 8M Mini 6

Deployment of Proposed EfficientNeXt on NXP *** 8M Mini

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6th international conference on Information and Computer Technologies, ICICT 2023

作者： Deokar, Abhishek El-Sharkawy, Mohamed Purdue School of Engineering and Technology Indianapolis Department of Electrical and Computer Engineering Indianapolis United States

ISBN: (纸本)9798350300956

Convolutional Neural Networks make tasks of computer vision like image classification and object tracking possible. The advances in accelerator hardware have made the progress in neural networks possible. Accelerator hardware is prevalent on desktops and high-end computing systems and may not always be available on low compute devices deployed on the Edge of internet of Things. The capabilities of neural network need to be ported to hardware that can run without accelerators. Benchmark setting neural networks like EfficientNet are too heavy for deployment on systems with low compute capabilities and can benefit from reduction in their memory footprint and optimized to improve their inference times. To this end we propose the design of EfficientNeXt and demonstrate its inference capabilities with reduced memory footprint (by 56%), increased accuracy and reduced inference time (by 30%) on an ARM based device. © 2023 ieee.

关键词： internet of things

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Asteroid image Inpainting Method based on Accelerated Diffusion Model 9

Asteroid Image Inpainting Method Based on Accelerated Diffus...

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9th international conference on Intelligent Computing and signal Processing, ICSP 2024

作者： Zheng, Yunyun Huang, Xiangyu Beijing Institute of Control Engineering Science and Technology Space Intelligence Control Laboratory Beijing China

ISBN: (纸本)9798350376548

To mitigate the threat of asteroid impact on life on Earth, non-nuclear kinetic energy high-speed impact has been identified as the most viable strategy. To ensure accurate impact on the asteroid's center of mass with maximum kinetic energy, high-precision and high-speed autonomous optical navigation is necessary during the probe's approach to the asteroid. Autonomous optical navigation is crucial due to the difficulty of using historical tracking data such as astrometry on the ground, given the long distance between the asteroid and the probe. The navigation image is used to extract the centroid of the target asteroid, with the center of gravity of the asteroid profile serving as the impact point to provide a stable impact direction. It is important to note that asteroids have irregular shapes, fast spin, and rapidly changing bright regions. The shadow area of the asteroid is constantly changing due to illumination, which causes bias in the impact point due to the incomplete profile. To complete the contour of the target asteroid, a method based on the accelerated diffusion model (ADM) is proposed to inpainting the shadow area. ADM is fast enough for mission and has been found to have the highest accuracy index and the lowest centroid deviation after restoration when compared to several advanced image restoration methods. © 2024 ieee.

关键词： Restoration

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A Framework for Segmentation of Thermal images using Unsupervised Fuzzy based Clustering Methods 10

A Framework for Segmentation of Thermal Images using Unsuper...

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10th international conference on Communication and signal Processing, ICCSP 2024

作者： Akilandeswari, A. Menaka, T. Ganesan, P. Rajasekaran, A. Chandrasekaran, B. Sajiv, G. Simats Saveetha School of Engineering Tamilnadu Chennai India Madha Engineering College Dept. of ECE Chennai Kundrathur India Vidya Jyothi Institute of Technology Dept. of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798350353068

image segmentation is a primary task in lots of computer vision applications, including thermal image segmentation. Thermal images are typically characterized by high levels of noise and low contrast, which can make segmentation challenging. In this paper, we propose an outline for thermal image segmentation using unsupervised fuzzy-based clustering methods. The proposed framework consists of three main steps: preprocessing, clustering, and post-processing. In the preprocessing step, the thermal image is enhanced to improve the contrast and remove noise. In the clustering step, a fuzzy clustering algorithm is used to cluster the pixels in the image into different regions based on colors. In the post-processing step, the results of the clustering algorithm are refined to improve the segmentation accuracy. The proposed work utilized three fuzzy based methods as Fuzzy C-Means clustering (FCM), Possiblistic Fuzzy C-Means clustering (PFCM) and Modified Fuzzy C-Means clustering (MFCM) for the thermal image segmentation. The proposed framework is evaluated on a number of thermal images. The outcome demonstrates that the projected framework can achieve good segmentation accuracy, even in the presence of noise and low contrast. The proposed framework is also robust to changes in illumination and can be used to segment thermal images with different levels of details. © 2024 ieee.

关键词： image segmentation

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Improving image Fidelity using Skip Connections Autoencoder 16

Improving Image Fidelity using Skip Connections Autoencoder

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16th international conference on Information technology and Electrical Engineering, ICITEE 2024

作者： Rumaksari, Atyanta Nika Hidayat, Risanuri Hartanto, Rudy Universitas Gadjah Mada Dept. of Electrical Engineering and Information Technology Yogyakarta Indonesia

ISBN: (纸本)9798350375817

This study presents an advanced autoencoder model with skip connections designed to enhance the image fidelity quality. Traditional methods often face challenges in preserving high-resolution details and textures, particularly in tasks involving noise reduction, super-resolution, and low-light enhancement. Our model leverages skip connections to maintain essential spatial information across different layers, effectively addressing the vanishing gradient problem and improving gradient propagation during training. We compare our model against several state-of-the-art methods, including the Overall Improved Autoencoder (OIAE), Cascade Decoders-based Autoencoders, and Edge-Aware Autoencoder Design, evaluating performance based on Mean Squared Error (MSE), Peak signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). Our autoencoder consistently achieves superior results, with MSE of 5.889e-05, PSNR consistently above 40 dB, and SSIM close to 1. These findings demonstrate the significant advantages of incorporating skip connections, which allow for better retention of high-resolution features and more accurate image reconstructions. © 2024 ieee.

关键词： image reconstruction

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3rd international conference on Advanced Computing and Applications, ICACA 2024

3rd International Conference on Advanced Computing and Appli...

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3rd international conference on Advanced Computing and Applications, ICACA 2024

ISBN: (纸本)9789819747986

The proceedings contain 47 papers. The special focus in this conference is on Advanced Computing and Applications. The topics include: Optimizing Task Offloading in internet of Medical Things systems: A Hybrid Fog-Cloud Approach with Actor-Critic Decision Making;solving Delivery Allocation for Logistic Network Using Quantum Annealing;The Combined ECC Scheme with Outer 3-Bit BEC and Inner SEC-DAEC Codes for FSO Communication System;analyzing Multisignature Scheme of Bitcoin based on Threshold Cryptography Guidelines;a Public Key Exchange Protocol Using Tropical Determinant for IoT Environment;Certificateless Verifiable Data Integrity Checking Scheme in Fog-CPSs Architecture;noPass—A Novel Passwordless Multi-authentication-based Approach for Secure Login;an Overview of the Discrete Logarithm Problem in Cryptography;QoS-Aware Decentralized Trustworthy Forensic Evidence Management Framework Using the internet of Vehicle Things (IoVT);implementation of Ethical Hacking—The Importance of Protecting User and System Data;Cryptanalysis of Two Correlation-based Digital Watermarking Schemes in DCT Domain;cryptanalysis of a Histogram-based Watermarking Framework;a Hybrid Deep Learning Framework for Text-Independent Automatic Speaker Recognition System;AMBTC-based High Capacity Data Hiding Scheme Exploiting PVD and BRP;The Impact of UX/UI Usability Constructs on Purchase Decisions for Mobile Food Ordering Applications in India;Breast Cancer Detection and Classification Using MF-FRFCM Segmentation and IGOA-ELM Model;audio Encryption Scheme Applying a 2D Cosine Sine Logistic Map;noisy Electronic Tongue signal Prediction for Tea Quality Estimation Using Autoencoder;a Chain Code-based Methodology for Loop Closure Detection in Digital images;A Hybrid Watermarking Scheme Using DWT and Haar Transform for image Authentication;leveraging Transfer Learning for Screening of Geriatric Depression;emotion-based Song Categorization with Support Vector Machines;filtering-based Movie Recommendati

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A PROBABILITY-based ALL-ZERO BLOCK EARLY TERMINATION ALGORITHM FOR QSHVC 30

A PROBABILITY-BASED ALL-ZERO BLOCK EARLY TERMINATION ALGORIT...

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30th ieee international conference on image Processing (ICIP)

作者： Wang, Dayong Lu, Xin Dufaux, Frederic Wang, Qianmin Li, Weisheng Hang, Bo Zhu, Ce Chongqing Univ Posts & Telecommun Chongqing Key Lab Big Data Bio Intelligence Chongqing Peoples R China De Montfort Univ Sch Comp Sci & Informat Leicester Leics England Univ Paris Saclay CNRS Cent Supelec Lab Signaux & Syst Paris France Chongqing Univ Posts & Telecommun Sch Comp Sci & Technol Chongqing Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Image Cognit Chongqing Peoples R China Hubei Univ Arts & Sci Comp Sch Xiangyang Hubei Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China

ISBN: (纸本)9781728198354

To seamlessly adapt to time-varying network bandwidths, Quality Scalable High-Efficiency Video Coding (QSHVC) is developed. However, its coding process is overwhelmingly complex, and this seriously limits its wide applications in realtime environments. Therefore, it is of great significance to study fast coding algorithms for QSHVC. In this paper, we propose a novel probability-based All-Zero Block (AZB) early termination algorithm for QSHVC. We observe that the generated residual coefficients follow the Laplace distribution if a CU is accurately predicted. based on this observation, we derive the sum of squared differences-based AZB decision condition. Second, the probability of each coding mode and coding depth being chosen as the best ones are combined with AZBs to derive the probability-based early termination condition. The experimental results show that the proposed algorithm can improve the average coding speed by 74.95% with a 0.26% increase in BDBR.

关键词： SHVC probability AII-Zero Block

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Deep Learning based Channel Estimation for Full-Duplex Backscatter Communication systems 5

Deep Learning based Channel Estimation for Full-Duplex Backs...

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5th international conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Jung, Chae Yoon Kang, Jae Mo Kim, Dong In Sungkyunkwan Univ SKKU Dept Elect & Comp Engn Dept Superintelligence Engn Suwon South Korea Kyungpook Natl Univ Dept Artificial Intelligence Daegu South Korea

ISBN: (纸本)9781665456456

A novel deep learning (DL) based channel estimation method is proposed for full-duplex backscatter communication systems to realize the wireless-powered sensor networks (WPSN) for internet of things (IoT). We aim to minimize the power consumption at a sensor node by reflecting the supplied power signal from an access point (AP), which is called backscatter communication. Moreover, by adopting the frequency-shifted modulation technique during backscatter transmission, full-duplex communication is performed between the AP and the sensor node. However, this incurs a problem that the uplink and downlink channels are cascaded, which results in degrading the performance of beamforming. In order to overcome this problem, we propose a novel channel estimation method that extracts separate uplink and downlink channels from the cascaded channels. We formulate the problem for joint channel estimation and pilot optimization, and then design the DL based channel estimator, which is composed of feedforward neural network(FNN) and convolutional neural network(CNN), for compensating non-linearity and non-convexity. Finally, we analyze the performance of the proposed DL based channel estimator compared to the conventional channel estimator.

关键词： Beamforming channel estimation (CE) deep learning (DL) full-duplex backscatter communication internet of things (IoT) wireless-powered sensor networks (WPSN)

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