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An Automated Hybrid Fusion Network for Poisson Noise Reduction in X-Ray Osteoarthritis images

An Automated Hybrid Fusion Network for Poisson Noise Reducti...

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international conference on Communication, Computing and internet of Things (IC3IoT)

作者： M Pavithra D Archana M Kanikha B Kavin G Kanishkar Rohith S Haritha Department of ECE Kongu Engineering College Erode TamilNadu Department of ECE PSG Institute of Technology and Applied Research Coimbatore Tamil Nadu

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

Denoising X-ray images is essential for improving medical image quality, especially in diagnosing conditions like knee osteoarthritis in Computer-Aided Diagnosis (CAD) systems. The presence of statistical noise, such as Poisson noise, can degrade X-ray image quality. While increasing radiation intensity and detector exposure time can help reduce this corruption, certain scenarios require low-dose detection and rapid response, such as security checks and urgent medical imaging assessments. Balancing noise reduction with preserving essential edge details poses a complex challenge in the denoising process. This study introduces a hybrid approach that combines two distinct denoising techniques: Fused Wavelet Transform and Autoencoder networks. The fusion strategy aims to leverage the strengths of both methods to enhance denoising performance and accuracy. Standard image quality metrics including Mean Absolute Error (MAE), Mean Squared Error (MSE), Peak signal-to-Noise Ratio (PSNR), Frequency based Error (FBE), Mean Squared Error (MSE), Structural Similarity Index Matrix (SSIM), and Contrast-to-Noise Ratio (CNR) are employed to evaluate performance. The proposed framework is rigorously evaluated, demonstrating significant improvements in denoising performance. Thus, the hybrid fusion method produces denoised images with higher detail and accuracy compared to conventional Convolutional Neural Network (CNN) based methods.

关键词： image quality Wavelet transforms PSNR Noise reduction Noise Telecommunication computing Convolutional neural networks

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Monitoring and Controlling Greenhouse Parameters by using IOT

Monitoring and Controlling Greenhouse Parameters by using IO...

引用

Intelligent signal Processing and Effective Communication Technologies (INSPECT), IEEE international conference on

作者： Sarita Samal Ravi Prakash Arijit Pal Lokeshwar Sandil Prasanta Kumar Barik Geetanjali Dei Dept. of EE KIIT DU India Dept. of MEE OUAT India

ISBN: (数字)9798350379525

ISBN: (纸本)9798350379532

Agriculture is the primary occupation in our country. But there are currently obstacles in agriculture because of the migration of people from rural to urban areas. Therefore, we use internet of Things-based smart agriculture solutions to solve the issue. This Paper includes the concept of internet of things (IoT) for Monitoring and controlling the different Parameters of greenhouse farming. The different parameters such as Temperature, humidity and Moisture percentage inside the soil are monitored for healthy crop production. Technological advancements are crucial in the agriculture business since they conserve time and labour. The created system comprises a mix of Arduino and several sensors to monitor greenhouse data in real time. The technology collects real-time crop data via sensors and transmits it to the user's mobile device. The user may monitor and regulate the temperature, lighting and irrigation in the greenhouse using a mobile smartphone.

关键词： Temperature sensors Temperature measurement Green products Crops Humidity Control systems Real-time systems internet of Things Monitoring Farming

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Digital Case image Compression Algorithm based on Deep Learning

Digital Case Image Compression Algorithm based on Deep Learn...

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Intelligent Algorithms for Computational Intelligence systems (IACIS), international conference on

作者： Benfeng Yu College of Literature Bohai University Jinzhou China

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

The result of deep learning lies in the acquisition of learners' depth of knowledge, which is mainly reflected in the development of higher-order thinking ability and the achievement of higher-order cognitive goals. With the vigorous development of deep learning, people begin to try to use deep learning technology to break through the bottleneck of traditional image compression methods. based on previous research results, this paper constructs a digital case image compression algorithm model based on deep learning, focusing on network training, quantization module and compression process. The mathematical formula of quality evaluation index of digital case image compression algorithm is derived, including PSNR, SSIM and MS-SSIM. JEPG algorithm and deep learning algorithm are compared and analyzed to illustrate the advantages of deep learning algorithm in the field of image compression. The experimental results show that the deep learning algorithm has obvious advantages in both subjective and objective evaluation.

关键词： Deep learning Training Productivity Technological innovation image coding Quantization (signal) Education Reflection Mathematical models Optimization

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Reference-Free Passive RF Imaging Using Near-Field Spatial Processing

Reference-Free Passive RF Imaging Using Near-Field Spatial P...

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Computing, internet of Things and Microwave systems (ICCIMS), international conference on

作者： Paul Brennan Kevin Chetty Wenda Li Shelly Vishwakarma Fabiola Colone Amin Amiri Dept of Electronic and Electrical Engineering University College London London UK Dept of Security and Crime Science University College London London UK Institute of Sensors Signals and Systems Heriot Watt University Edinburgh Scotland Dept of Electronics and Computer Science University of Southampton Southampton UK Department of Information Engineering Electronics and Telecommunications Sapienza University of Rome Rome Italy

ISBN: (数字)9798350351736

ISBN: (纸本)9798350351743

Passive radar imaging has been extensively studied and is based on an illuminator-of-opportunity, such as a wireless access point, providing a signal that scatters from targets and is incident on a receiving node(s) in order to infer information on the range and velocity of the target scene. Such systems universally require reference signal regeneration, from a dedicated channel, that is cross-correlated with the received signal in order to extract the range/Doppler information of the target. This paper presents one of several techniques developed by the authors to achieve passive radar (or RF) imaging without any requirement for extraction of the reference signal. The concept is analogous to optical systems in which various source(s) provide general illumination of a target scene, the scattered signals of which are gathered and processed at an optical sensor in order to reconstruct the image, but without any requirement to extract the illumination (reference) source itself. Such an approach offers numerous practical advantages in achieving imaging from a single passive sensor without the additional requirement of precise, or indeed any, regeneration of the illuminating source: a reference-free approach. This paper presents one such technique based on sampling of the complex signal distribution over an antenna aperture and near-field processing to form a two/three-dimensional reconstruction of the target scene. The fundamental principles of the technique are described along with analysis of basic performance limits. Modelling is presented to illustrate the capability of the technique, which is validated by experimental measurement with a WiFi access point-based prototype system.

关键词： Radio frequency Passive radar Imaging Prototypes Radar imaging Optical sensors Optical scattering Spatial resolution Optical signal processing Wireless fidelity

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Research on Visual Communication of Graphic Design based on Machine Vision 3rd

Research on Visual Communication of Graphic Design Based on ...

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3rd international conference on 3D Imaging Technologies - Multidimensional signal Processing and Deep Learning (3DIT-MSP and DL)

作者： Zhou, Qihao Liu, Teng Wonkwang Univ Iksan South Korea

ISBN: (纸本)9789811924484;9789811924477

Visual communication graphic design as a difficult point in modern technology research, its original intention is to use visual graphics to transmit some ideas or ideological content to people, belongs to the visual image with creative thinking, people can according to their own visual sense to obtain the special language form contained in it. Whether it is commercial circulation or social culture, graphic design of visual communication has shown a profound influence. Therefore, in this paper, the machine vision graphics processing system is applied to the visual communication graphic design, and the system structure, functional modules, design process and other contents are simply understood, and according to the injection mold trademark design and processing practice cases are verified and analyzed. The final results prove that the visual communication graphic design system with machine vision as the core has played a positive role in the current technological development.

关键词： Machine vision Visual communication Graphic design CAD The image processing

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Parking Space Monitoring – A LoRa based Approach

Parking Space Monitoring – A LoRa Based Approach

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Annual Information technology, Electromechanical Engineering and Microelectronics conference (IEMECON)

作者： B.C. Mallikarjun G Anantha Krishna B.V. Mahantesha K.T. Monish E Kishore Dept. of ETE Siddaganga Institute of Technology Tumkur Karnataka state India

A huge growth of big cities, the number of vehicles are increased significantly and large buildings and parking lots have been built. Smarter parking systems need to be developed to assist drivers in finding nearby parking spaces available. Various research efforts have been shown in developed countries in such system implementation. There are four main types of systems of parking management: wired sensor based, image based, counter based, and based on wireless sensors. This paper combines computer vision and LoRa wireless technology and worked on image-based system to find empty slot in the parking lot. Following the first edge detection category, includes front/rear pixel rate, closed contour density, and edge density. For all car parks to determine if the vehicle exists or not and to update this information to the user using wireless technology in a way that saves power and performance offline while minimizing system maintenance costs.

关键词： Wireless communication Wireless sensor networks Smart cities image edge detection Streaming media Cameras Monitoring

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Phase Retrieval: Application to Audio signal Reconstruction 19

Phase Retrieval: Application to Audio Signal Reconstruction

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19th IEEE international Multi-conference on systems, signals and Devices, SSD 2022

作者： Bedoui, Raja Abdelmalek Mnasri, Zied Benzarti, Faouzi Ecole Nationale d'Ingénieurs de Tunis University Tunis El-Manar Signal Image and Technology of Information Laboratory Tunisia Ecole Nationale d'Ingénieurs de Tunis University Tunis El-Manar Electrical Engineering Department Tunisia

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

Theoretically, phase retrieval is an efficient method for signal reconstruction given only the magnitude spectrum of the short-term Fourier transform (STFT). This topic has recently regained popularity due to its utility in a variety of applications such as compressive sensing, speech synthesis, speech enhancement, source separation, and so on. As a result, based on an explicit relationship between STFT magnitude and phase, this paper presents an efficient algorithm for audio signal reconstruction using phase retrieval from the STFT magnitude spectrum. The standard metrics in signal reconstruction, such as time domain segmental signal-to-noise ratio (segSNR), time-frequency domain signal-to-error ratio (SER), and cepstrum-related distance measures, such as log-likelihood ratio (LLR), Itakura-Saito distorsion (IS), and cepstrum distance, are used to perform an objective evaluation. The results support the proposed approach's improvement. © 2022 IEEE.

关键词： signal reconstruction

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MEDIAN: Adaptive Intermediate-grained Aggregation Network for Composed image Retrieval

MEDIAN: Adaptive Intermediate-grained Aggregation Network fo...

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international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Qinlei Huang Zhiwei Chen Zixu Li Chunxiao Wang Xuemeng Song Yupeng Hu Liqiang Nie School of Software Shandong University Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) School of Computer Science and Technology Shandong University School of Computer Science and Technology Harbin Institute of Technology (Shenzhen)

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The Composed image Retrieval (CIR) task aims to retrieve a target image that meets the requirements based on a given multimodal query (includes a reference image and modification text). Most existing works align multimodal semantics at both local and global granularity. However, they have failed to consider the mining of semantic correspondences at the intermediate-grained level, which has resulted in sub-optimal model performance. In this paper, we propose an adaptive interMEDiate-graIned Aggregation Network (MEDIAN). Compared with the conventional CIR models, MEDIAN is capable of generating intermediate-grained feature aggregation supervised signals and constructing graph attention networks to extract intermediate-grained features. Concurrently, MEDIAN also devises cross-modal semantic correspondence aligning guided by the target image, which in turn enables accurate multi-grained feature composition. The superiority of MEDIAN is demonstrated by extensive experiments on three benchmark datasets. Our code is available at https://***/***/.

关键词： Adaptation models Adaptive systems Accuracy Codes Semantics image retrieval Benchmark testing signal processing Feature extraction Speech processing

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Cooperative Physical Layer Authentication for Massive MIMO Machine-Type Communications 23

Cooperative Physical Layer Authentication for Massive MIMO M...

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23rd IEEE international conference on Communication technology, ICCT 2023

作者： Zhang, Haotian Wang, Junjie Han, Gangtao Wang, Ning School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou450001 China Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China

ISBN: (纸本)9798350325959

Aiming to improve the identity security of massive machine-type communications networks, a two-user cooperative physical layer authentication (PLA) scheme is proposed for the uplink transmission of a massive multiple-input multiple-output (MIMO) systems. In the proposed scheme, two single-antenna users synchronously transmit signals to the base station which is equipped with a large number of antennas, and fast varying channels are considered. A space-time modulation scheme is adopted for the two users to implement cooperative PLA, in which tags are selectively embedded into the transmitted signals based on the bit-relationships between the tags and the messages in order to improve the covertness of tags. A minimum Riemannian distance detector is proposed to implement the tag detection, while a fast noncoherent maximum likelihood (ML) detector is introduced to carry out the messages estimation. Binary hypothesis test is carried out for authentication by comparing the detected tags to the regenerated ones, in which the PLAs of the two users are handled as a whole. The closed-form bit error probability of the message is derived, while the authentication performance is analyzed. Computer simulation results demonstrate that the proposed scheme performs better on signal detection as well as identity authentication. © 2023 IEEE.

关键词： cooperative physical layer authentication massive MIMO noncoherent detection selective tag

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Visual Multi Scene Intelligent Car Service Platform based on internet of Things technology 1

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11th international conference on Communications, signal Processing, and systems, CSPS 2022

作者： Pan, Guoqing School of Information Engineering Suzhou University Anhui Suzhou234000 China

ISBN: (数字)9789819926534

ISBN: (纸本)9789819926527

The visual multi scene intelligent car service platform based on internet of things technology is different from any previous machine idea. It is specially designed to serve an industry or a field. What we want to achieve here is a multi scene service state, and switching scenes without switching machines (only switching conversion method). At the same time, in order to meet this requirement, the traditional centralized design scheme can not be used to arrange all tasks in the machine. Therefore, the hardware level is separated from the software level for step-by-step processing, which will not only reduce the pressure of the hardware machine, but also improve its processing efficiency. Further, its processing capacity is no longer limited by the underlying hardware, but determined by the performance of the upper computer, After having a very powerful upper computer, it can realize the control mode of multi lower computer management. At the same time, it can adopt the scheme of time-sharing processing to deal with the multi lower computer, so as to meet its various performance requirements. In this way, we can complete the service mode of more scenarios under the current technical force, and only adopt a machine mode, a scalable and scalable smart car service platform whose efficiency can be improved at any time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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