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Optimization and Design of Coding Algorithm for Monitoring System based on Embedded Structure 7

Optimization and Design of Coding Algorithm for Monitoring S...

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7th international conference on Intelligent Computing and signal Processing, ICSP 2022

作者： Huang, Rubing Zhao, Lianyi Anhui Vocational and Technical College School of Information Engineering Hefei China Anhui Water Resources and Hydropower Vocational and Technical College School of Mechanical & Electrical Engineering Hefei China

ISBN: (纸本)9781665478571

In view of the problems of large transmission delay, low video image compression rate, and high network transmission overhead in traditional monitoring systems. According to the characteristics of ARM platform and H.264 encoding algorithm, an algorithm optimization method based on x264 encoder embedded platform is proposed. The New Three-step Search method is used to realize motion compensation prediction encoding. based on streaming media technology, The RTP and RTSP protocol realizes the packaging and real-time transmission of video stream data. The optimized encoder is applied to the embedded video monitoring system, which effectively improves the video encoding efficiency of the system. © 2022 IEEE.

关键词： signal encoding

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37th international conference on Advanced Information Networking and Applications, AINA 2023

37th International Conference on Advanced Information Networ...

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37th international conference on Advanced Information Networking and Applications, AINA 2023

ISBN: (纸本)9783031290558

The proceedings contain 160 papers. The special focus in this conference is on Advanced Information Networking and Applications. The topics include: D-insta: A Decentralized image Sharing Platform;simulation Modeling of Human Aortic Valve Blood Flow;ramification of Sentiments on Robot-based Smart Agriculture: An Analysis Using Real-Time Tweets;the Digital Humanities Trend in Chinese Film History: A Case Study of Filmmaker Lvban;A Tool for Creation of Virtual Exhibits Presented as IIIF Collections by Intelligent Agents;recommender systems in the Museum Sector: An Overview;Towards the Enrichment of IIIF Framework with Semantically Annotated and Geo-Located images;Comparison of ML Solutions for HRIR Individualization Design in Binaural Audio;Performance Analysis of a BESU Permissioned Blockchain;AI-Powered Drone to Address Smart City Security Issues;range Proofs with Constant Size and Trustless Setup;sensorless Predictive Maintenance: An Example on a ‘Not 4.0’ Coffee Machine Production Process;An Integrated System for Vibration Suppression Using Fuzzy Control and 2D-LiDAR;attendance System via internet of Things, Blockchain and Artificial Intelligence technology: Literature Review;an Overview and Current Status of Blockchains Performance;AgriBIoT: A Blockchain-based IoT Architecture for Crop Insurance;distribution of the Training Data Over the Shortest Path Between the Servers;a Decentralized Architecture for Electric Vehicle Charging Platform;services and Operations of Electric Vehicle System by Virtual Power Plant in Rural Area;a Triangulation based Water Level Measuring System for a Water Reservoir Tank;A System Architecture for Heterogeneous Time- Sensitive Networking based on SDN;a Parking System based on Priority Scheme;DTAG: A Dynamic Threshold-based Anti-packet Generation Method for Vehicular DTN;prediction in Smart Environments and Administration: Systematic Literature Review;Optimal and Suboptimal Routing Protocols for WSN;CL-DECCM-SA: A Cluster-based Delauna

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Semi-Supervised Principal Neighbourhood Aggregation Model For Sar image Classification

Semi-Supervised Principal Neighbourhood Aggregation Model Fo...

引用

international IEEE conference on signal-image Technologies and internet-based System

作者： Mohib Ullah Zolbayar Shagdar Habib Ullah Faouzi Alaya Cheikh Department of Computer Science Norwegian University of Science and Technology Norway Faculty of Science and Technology (REALTEK) Norwegian University of Life Sciences (NMBU) Norway

Graph neural networks (GNNs) are researched extensively as effective models for representing data in a graph structure and extracting important neighbourhood features. This paper explored a GNN model named Principal Neighbourhood Aggregation (PNA) for Synthetic-aperture radar (SAR) image classification. Given the low availability of SAR image data, specially labelled ones, we incorporate a semi-supervised learning strategy named MixMatch with PNA architecture. Furthermore, we propose an augmentation technique specific to SAR images that exploit the physical properties of image content and significantly improve the performance of both supervised and semi-supervised training paradigm. Additionally, we tested the algorithm on benchmark image classification datasets, including CIFAR, MNIST, STL10 and achieved promising results.

关键词： Training Benchmark testing Semisupervised learning Feature extraction Radar polarimetry Presence network agents Graph neural networks

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A MEMS Cone-shaped Helix Antenna for THz Applications Using ANN 7

A MEMS Cone-shaped Helix Antenna for THz Applications Using ...

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7th international conference on image and signal Processing and their Applications, ISPA 2022

作者： Chetioui, Mohammed Boudkhil, Abdelhakim Damou, Mehdi Bouallem, Mansouri Bouasria, Fatima Benahmed, Nasreddine Laboratory of Electronics Advanced Signal Processing and Microwave University of Dr. Tahar Molay Saida Algeria Laboratory of Telecommunications University of Abou-Bekr Belkaid Tlemcen Algeria Laboratory of Technologies of Communications Dr.Tahar Moulay University Saida Algeria

ISBN: (纸本)9781665480420

The role of Micro-Electromechanical systems (MEMS) antennas in Terahertz (THz) areas has recently graduated due to the modern Computer Aided Design (CAD) techniques. The very special demand for novel MEMS antennas with high performance for wide THz frequency range grows for the foreseeable future, and requires effective optimization processes of improving already proposed designs. This paper describes for the THz wireless access systems a new design of a cone-shaped helix antenna based on MEMS technology. The antenna is developed using tree-dimensional High Frequency Structure Simulator (3D-HFSS) for modal electromagnetic analysis, and accurate automatic strategists (Artificial Neural Network ANN) for active optimization. The optimization strategy aims to vary the antenna geometry and maximize it response for the selective frequency band with a high accuracy from Finite Element Method (FEM). The MEMS helix antenna presents very low return losses of less than -63dB at a resonance frequency equals to 3.59 THz, and less than -20dB for a wide frequency range from 3.12 to 4 THz. Excellent antenna performance and high structure precision are finally achieved by modifying and rectifying different tuneable parameters embedded in silicon platform including helix variables. © 2022 IEEE.

关键词： MEMS

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Revolutionizing Agriculture with IoT: Innovation in Food and Farming technology

Revolutionizing Agriculture with IoT: Innovation in Food and...

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international conference on signal Processing, Communication, Power and Embedded System (SCOPES)

作者： Swaroop Sualsingh Arunabha Pal Vemu Sudham Chunchu Suchith Kumar Pilli Manasa Priyanka Nandi Department of Soil Science Centurion University of Technology and Management Paralakhemundi Odisha India Department of Agronomy School of Agriculture SR University Warangal Telengana India Department of Agronomy K.L. College of Agriculture K.L. University Andhra Pradesh India Department of Horticulture Birsha Agricultural University

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

This study explores the digital transformation of agriculture, using road maps to illustrate the transition from industrial and agricultural revolutions to a prosperous future. Precision agriculture, which includes modern agriculture, and Agriculture 4.0 are managed via sectors that involve logistics, management, estimation, and monitoring. AI and decision support systems are given as examples of digital technology applications. flexible sensor technologies, present-time tracking systems that track the internet of things (IoT)-based irrigation, and fertilization systems that lower water and fertilizer losses in agricultural fields and climate control environment. The ATLAS and DEMETER projects utilize sensor-based digital platforms to enhance water use efficiency and sustainable agriculture. These technological advancements help overcome socioeconomic and environmental challenges, ensuring a sustainable future for agriculture.

关键词： Smart agriculture Decision support systems Technological innovation Digital transformation Agriculture internet of Things Sustainable development Artificial intelligence Farming Meteorology

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Transformer based image Dehazing

Transformer based Image Dehazing

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international IEEE conference on signal-image Technologies and internet-based System

作者： Patricia L. Suárez Dario Carpio Angel D. Sappa Henry O. Velesaca ESPOL Polytechnic University Guayaquil Ecuador Computer Vision Center Barcelona Spain

This paper presents a novel approach to remove non homogeneous haze from real images. The proposed method consists mainly of image feature extraction, haze removal, and image reconstruction. To accomplish this challenging task, we propose an architecture based on transformers, which have been recently introduced and have shown great potential in different computer vision tasks. Our model is based on the SwinIR an image restoration architecture based on a transformer, but by modifying the deep feature extraction module, the depth level of the model, and by applying a combined loss function that improves styling and adapts the model for the non-homogeneous haze removal present in images. The obtained results prove to be superior to those obtained by state-of-the-art models.

关键词： image quality Adaptation models Computational modeling Computer architecture Transformers Feature extraction image restoration

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Design and Implementation of Fish image Recognition System based on Transfer Learning 14

Design and Implementation of Fish Image Recognition System B...

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14th international conference on signal Processing systems, ICSPS 2022

作者： Li, Wanghua Zhang, Zhenkai Wang, Yuhao Yu, Wangyang Ocean College Jiangsu University of Science and Technology Zhenjiang212100 China Wuhan Maritime Communication Research Institute Department of Communication Wuhan430223 China

ISBN: (纸本)9798350336313

In order to solve the problems existing in the traditional artificial recognition methods, a design method of fish image recognition system based on transfer learning is proposed to realize the intelligent recognition of Marine fish images. Firstly, the system selects five basic deep learning pre-training models as BaseNet, and carried out experiments by using data image preprocessing, network model structure fine-tuning, training parameters fine-tuning and other methods. Secondly, in order to better present the recognition results, the migration FAST-SCNN pre-training model is used to extract the boundary contour features, so that the system can not only recognize the categories of fish images, but also segment the boundary contour of fish images. The front-end of the system uses *** framework for page building, and the back-end uses the Flask framework based on Python language for deployment. By calling the trained model files such as recognition and segmentation, functions such as fish recognition, contour prediction and page presentation are realized. Finally, experiments are carried on the preprocessed F4K dataset, and the experimental results show that the comprehensive performance of migrated InceptionV3 method is the best, and its recognition accuracy is 99.49%. Compared with T-inceptionV3 method, the recognition accuracy is improved by 5.16%. The proposed design and implementation method of the system provides a feasible idea for the application of fish image recognition technology in the web, which can be used for reference by Marine researchers and developers. © 2022 IEEE.

关键词： Deep learning

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internet of Things Enabled Blockage Detection in Micro-Irrigation System by Using Drones

Internet of Things Enabled Blockage Detection in Micro-Irrig...

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Electronics and Sustainable Communication systems (ICESC), 2020 international conference on

作者： R. Vijayakumar S. Divyapriya R. Satheesh Kumar C. Ramya S. Sharmila Department of EEE SNS College of Technology Coimbatore Department of EEE Karpagam Academy of Higher Education Coimbatore

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

Drip irrigation systems, while efficient in water usage, often suffer from clogged emitters, leading to crop loss. To address this challenge, a drone-based solution is proposed. Equipped with image processing capabilities and controlled by loT, the drone can identify clogged emitters and potentially clear obstructions. Additionally, the system can collect salty water from the irrigation system, contributing to overall water management. This integrated approach aims to optimize water utilization, enhance crop yield, and mitigate the impacts of water scarcity in agriculture.

关键词： Irrigation Cloud computing Communication systems image processing Memory management internet of Things Monitoring Crop yield Drones Diseases

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An AI Decision System to Predict Lung Nodules through Localization from Chest X-ray images 9

An AI Decision System to Predict Lung Nodules through Locali...

引用

9th international conference on signal Processing and Communication, ICSC 2023

作者： Koyyada, Shiva prasad Singh, Thipendra P. School of Computer Science UPES University Dehradun India uGDXIT Hyderabad India School of Computer Science Engineering and Technology Bennett University NCR Delhi India

ISBN: (纸本)9798350383201

The objective of this research is to design an Artificial Intelligence (AI) decision system that helps medical practitioners diagnose lung disease with more probability. Between the 1970s and 1990s, clinical image analysis was carried out by fusing low-level pixel processing (edge and line detectors, region expansion) with mathematical modeling (fitting lines, circles, and ellipses) to develop compound rule-based systems that dealt with particular tasks. In the 1990s the handwritten recognition task adapted Convolutional neural networks(CNN) and achieved the remarkable success that has laid the road for CNNs. The Chinese of Wuhan, in the Hubei Province, saw an epidemic of the coronavirus illness 2019 (COVID-19), which was unleashed by the SARS-CoV-2. The World Health Organization declared the pandemic a public health emergency of worldwide significance on January 30, 2020. Over three years have passed since the worldwide struggle against the COVID-19 epidemic began. One of the quickest methods to diagnose patients is to use computer-aided diagnosis (CAD) and deep learning techniques on radiography and radiology images. With this, everyone's focus has turned to lung disease detection such as tuberculosis and lung cancer through Chest X-ray images with state-of-the-art methods such as CNNs. However, these fail to explain the reason for making such a decision. This work focuses on this aspect of determining region of interest features with a process of localization while predicting lung nodules in two stages with the help of an explainable artificial method. © 2023 IEEE.

关键词： image segmentation

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A Peach Maturity Detection Algorithm based on YOLOV5 Attention Mechanism 2

A Peach Maturity Detection Algorithm Based on YOLOV5 Attenti...

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2nd international conference on Machine Learning and Intelligent systems Engineering, MLISE 2022

作者： Zhang, Jiong Ye, Caizeng Shandong Institute Of Commerce And Technology School Jinan250103 China

ISBN: (数字)9781665492461

ISBN: (纸本)9781665492461

With the rapid development of computer vision technology, the original method of rapid non-destructive testing of peach maturity has been unable to meet the management requirements, and the management efficiency and accuracy cannot meet the daily needs. based on the above reasons, this paper proposes a peach maturity detection algorithm based on YOLOV5 attention mechanism. The algorithm shows the whole process of management through data collection, model training, and model application. It adopts the prototype method and the object-oriented system development method. The external camera network configuration is used to connect the image display interface of the web display screen, and the server is used as the support and the bearer network is used as the system basis. Through the experimental results, it is found that the new algorithm proposed in this paper has obvious advantages compared with other comparison algorithms, and the experimental results more precise. © 2022 IEEE.

关键词： signal detection

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