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检索条件"任意字段=5th International Conference on Signal Processing and Machine Learning, SPML 2022"

共 777 条记录，以下是581-590 订阅

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SmartMeter: An Automatic Water Metering System using Computer Vision and ARIMA-based machine learning 22

SmartMeter: An Automatic Water Metering System using Compute...

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Proceedings of the 2022 5th international conference on machine learning and Natural Language processing

作者： Felix Fl Lin Yu Ys Sun Arnold O. Beckman High School USA Computer Science Department California State Polytechnic University USA

ISBN: (纸本)9781450399067

Having access to sufficient water usage data real-time is crucial not only to finding water leaks and preventing water bills (which can cost up to thousands of dollars) but also to tracking water usage and savings. However, to record a California household's water usage, a worker from the respective water district must personally check the water meter in order to update the data at a monthly frequency. this is because the current water infrastructure in California is outdated while also being expensive to replace. Additionally, while certain cities such as San Jose has Advanced Metering Systems for water installed, due to a lack of budget, it can be difficult for government agencies to develop a solution that can be implemented statewide, then nationwide, in an estimated 2-3 years from now. this paper proposes an IoT-based smart water monitor that utilizes computer vision to record water data, then compares the data's deviance from the predicted usage to check for water leaks. We applied our application to monitoring the water usage of my own household and conducted a qualitative evaluation of the approach. the results show that the water monitor is an effective and affordable way to water management.

关键词： Automated metering infrastructure

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Real-Time signal processing using AI Integrated Framework for Color and Drawing in Gesture Recognition

Real-Time Signal Processing using AI Integrated Framework fo...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Geerija Lavania Vivek Arya Neha Sharma Mamoon Rashid Shaik Vaseem Akram Artificial Intelligence & Data Science Department JECRC Jaipur Rajasthan India Dept of Electronics and Communication Engineering Gurukula Kangri (Deemed to be University) Haridwar India Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India Department of Computer Engineering Vishwakarma University Pune India Uttaranchal Institute of Technology Uttaranchal University Dehradun India

In the realm of image processing and pattern recognition, writing with gestures in the air has grown in popularity and difficulty over the past few years. It contributes significantly to the creation of automation processes and can improve human-machine communication in a range of systems. Many studies focus on cutting-edge methods and techniques that will expedite processing while preserving a high level of identification accuracy. Internally, the area of computer vision considers object tracking to be crucial. Object tracking techniques are credited to modern computers, easy access to good-looking, affordable video cameras, and automated video analytics requirements. the video analysis technique generally consists of three fundamental steps: first, recognizing the object, second, tracking its movement from frame to frame, and third, assessing the behavior of that object. Each of the four takes into account a separate issue: choosing the best item representation, choosing the tracking function, purchasing the item, and tracking the item. Numerous real-world applications, such as autonomous monitoring, video identification, and vehicle navigation, depend heavily on object-tracking algorithms. this area is utilized by the research, which focuses on it to create a prospective text-to-text converter transition. this Research occasionally works as a freelance journalist. Your fingerprint will be tracked by a computer. the created text can be copied and used for a variety of things, including emails and SMS. For the deaf, it will be a potent means to establish this connection. By removing the need for writing, an efficient communication system decreases the use of the phone and laptop.

关键词： Portable computers Navigation Visual analytics signal processing algorithms Writing signal processing Real-time systems

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A study on the Application of Bio-Inspired Algorithms in the Diagnosis of Efficient Ultrasound Liver Images

A study on the Application of Bio-Inspired Algorithms in the...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Manish Kumar Yadav Akshat Singh Arun Singh Shruti School of Computer Science and Engineering Lovely Professional University Phagwara India Department of Computer Science and Engineering Lovely Professional University Phagwara Punjab India

Maintaining physical and mental well-being is a major concern for every person. Liver disease is one of the worst illnesses that affects people throughout. Modern hospitals have the latest in data collecting and transmission devices, allowing for smooth information exchange across different computerized systems. In spite of this, making a correct diagnosis of an illness has always been a vital part of the medical profession. Diseases of the liver are difficult to diagnose early on because the organ might appear healthy while nevertheless being severely damaged. Indeed, the patient’s life expectancy can be significantly improved with early detection of liver *** artificial intelligence and optimization algorithms have lately earned a lot of attractiveness in medical diagnostics which are employed to identify the ailment using the gathered data. there has been a rise in the use of CAD (Computer Aided Diagnosis) techniques in the medical field as a result of their increased efficiency. Specialists in the creation of cutting-edge algorithms now guarantee a higher degree of accuracy in the detection and diagnosis of illnesses. As a result, using improvised algorithms can address the core problem of predicting and identifying the disease at an early *** research begins with an investigation of the integration of machine learning with classification optimization strategies. Due to its non-persistent nature, cheap cost, portability, and suitability for classification methods, ultrasound imaging is frequently employed in medical diagnostics. In this procedure, liver illness is classified using image processing techniques based on computer-aided design. In this research work, we have conducted a comprehensive study on the application of Bio-Inspired Algorithms in the Diagnosis of Efficient Ultrasound Liver Images. this evaluation was carried out using the Bio-Inspired Algorithms Liver Image Analysis. Additionally, this will assist other researchers in beco

关键词： Ultrasonic imaging machine learning algorithms Liver machine learning Prediction algorithms Classification algorithms Medical diagnosis

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26th international Symposium on VLSI Design and Test, VDAT 2022

26th International Symposium on VLSI Design and Test, VDAT 2...

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26th international Symposium on VLSI Design and Test, VDAT 2022

ISBN: (纸本)9783031215131

the proceedings contain 48 papers. the special focus in this conference is on VLSI Design and Test. the topics include: Impact of Temperature on NDR Characteristics of a Negative Capacitance FinFET: Role of Landau Parameter (α);preface;FEM Modeling of thermal Aspect of Dielectric Inserted Under Source & Drain of 5 nm Nanosheet;i-MAX: Just-In-Time Wakeup of Maximally Gated Router for Power Efficient Multiple NoC;quantum Tunnelling and themonic Emission, Transistor Simulation;electro-thermal Analysis of Vertically Stacked Gate All Around Nano-sheet Transistor;Fabrication, Optimization and Testing of Photoconductively Tuned SAW Device Using CBD Method;High Resolution Temperature Sensor signal processing ASIC for Cryo-Cooler Electronics;Low Power, Wideband SiGe HBT LNA Covering 57-64 GHz Band;Four Differential Channels, Programmable Gain, Programmable Data Rate Delta Sigma ADC;Low Power Dual-Band Current Reuse-based LC-Voltage Controlled Oscillator with Shared Inductor for IoT Applications;Aging Resilient and Energy Efficient Ring Oscillator for PUF Design;a GaN Based Reverse Recovery Time Limiter Circuit Integrated with a Low Noise Amplifier;differential Multi-bit through Glass Vias for three-Dimensional Integrated Circuits;novel Configuration of Multi-mode Universal Shadow Filter Employing a New Active Block;Highly Non-linear Feed-Forward Arbiter PUF Against machine learning Attacks;An Online Testing Technique for the Detection of Control Nodes Displacement Faults (CNDF) in Reversible Circuits;An Approach Towards Analog In-Memory Computing for Energy-Efficient Adder in SRAM Array;MANA:Multi-Application Mapping onto Mesh Network-on-Chip using ANN;Metastable SR Flip-Flop Based True Random Number Generator Using QCA Technology;Hardware Design of Two Stage Reference Free Adaptive Filter for ECG Denoising;A Reconfigurable Arbiter PUF Based on VGSOT MTJ;Low Cost Hardware Design of ECC Scalar Multiplication.

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A Composite Image processing Technique to Enhance Segmentation of Ultrasound Images 22

A Composite Image Processing Technique to Enhance Segmentati...

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Proceedings of the 2022 5th international conference on Digital Medicine and Image processing

作者： Mahmood Alzubaidi Marco Agus Khaled Al-thelaya Michel Makhlouf Khalid Alyafei Mowafa Househ College of Science and Engineering Hamad Bin Khalifa University Qatar Departments of gynecology Sidra Medicine Qatar Pediatrics emergency medicine Sidra Medicine Qatar

ISBN: (纸本)9781450397643

In ultrasound images, the speckle noise phenomenon is a typical issue that limits the accuracy of the images obtained from any quantitative measurement. Noise elimination in ultrasound images in the pre-processing stage is an important step to make the image fit for the following steps involved in image segmentation. However, various noises produce a range of significant impacts on the quality of the image and thus tend to affect the interpretation of neural networks. In this study, 35 different image processing techniques, including denoising, feature descriptor, edge detection, miscellaneous, clustering, morphological, sharpening, and composite techniques were used to determine the most optimal ultrasound image in order to improve the segmentation of ultrasound images. the performance of image processing techniques was compared using a statistical parameter, peak signal-to-noise ratio (PSNR). All techniques were examined on deep learning segmentation approach. the segmentation performance was evaluated using mean intersection over union (mIoU) and mean pixel accuracy (mPA). the results showed that the composite image technique (FancyPCA + Bilateral + Gabor) slightly enhanced the segmentation performance, with the most ideal mIoU 0.96893%, mPA 0.97831%, and average PSNR 53.034 dB.

关键词： Denoising Fetal head Filtering Image processing Segmentation Ultrasound

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A Clinical support system for Prediction of Heart Disease using machine learning Techniques 5

A Clinical support system for Prediction of Heart Disease us...

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5th international conference on Advanced Technologies for signal and Image processing (ATSIP)

作者： El Hamdaoui, Halima Boujraf, Said Chaoui, Nour El Houda Maaroufi, Mustapha Univ Sidi Mohamed Ben Abdellah Fac Med Clin Neurosci Lab Dept Biophys & Clin MRI Methods Fes Morocco Univ Sidi Mohamed Ben Abdellah Transmiss & Treatment Informat Lab Fes Morocco

ISBN: (数字)9781728175133

ISBN: (纸本)9781728175133

Heart disease is a leading cause of death worldwide. However, it remains difficult for clinicians to predict heart disease as it is a complex and costly task. Hence, we proposed a clinical support system for predicting heart disease to help clinicians with diagnostic and make better decisions. machine learning algorithms such as Naive Bayes, K-Nearest Neighbor, Support Vector machine, Random Forest, and Decision Tree are applied in this study for predicting Heart Disease using risk factors data retrieved from medical files. Several experiments have been conducted to predict HD using the UCI data set, and the outcome reveals that Naive Bayes outperforms using both cross-validation and train-test split techniques with an accuracy of 82.17%, 84.28%, respectively. the second conclusion is that the accuracy of all algorithm decrease after applying the cross-validation technique. Finally, we suggested multi validation techniques in prospectively collected data towards the approval of the proposed approach.

关键词： Heart disease clinical decision systems machine learning UCI heart disease data set

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Development of Smart Motion Biosensor for Power Management and Monitoring

Development of Smart Motion Biosensor for Power Management a...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Aishwary Awasthi Rini Saxena Department of Mechanical Engineering Sanskriti University Mathura Uttar Pradesh India Department of Computer Science & Engineering Chandigarh Engineering College Jhanjeri India

Advanced smart residential buildings place a major emphasis on monitoring and energy optimization that is both affordable and efficient. the Pyro electric Infrared Sensor (PIR) is a great privacy-preserving, non-intrusive surveillance tool with a tiny, robust design that can easily detect the presence of people or animals. When a human or animal body is detected in a sensor’s surveillance zone, a discrete ON/OFF selection of the PIR sensor is often commonly used to control lights, electrical devices, and/or to trigger the alarm. the decision-making process used in this study is based on the analogue pattern acquired from a PIR sensor. A sensor’s Field of View (FoV) analogue pattern and accompanying wave shape may provide important details about the movement’s direction, approximation of distance, and other factors. Algorithms for time-series pattern analysis and machine learning may be used to increase the accuracy of estimate. Finally, a cheap LoRa module may wirelessly link the sensor module and the main control PC in order to record movement analytics. For the most effective administration of resources and logistics, the information may be saved. In comparison to peer camera-based monitoring, which consumes more computing power, costs more money, and, most crucially, invades privacy, the approach may be quite successful. Seniors in engineering and technology participated as a component of their final research experience. they worked on creating 3D printed modules, PIR circuit designs, and motion capture for backend processing. this was a professional engineering project that included cross-disciplinary learning.

关键词： Privacy three-dimensional displays machine learning algorithms Animals Shape Surveillance Power system management

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Method of Graphical User Interface Adaptation Using Reinforcement learning and Automated Testing 21

Method of Graphical User Interface Adaptation Using Reinforc...

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Proceedings of the 2021 5th international conference on Natural Language processing and Information Retrieval

作者： Victor Fyodorov Andrey Karsakov National Center of Cognitive Research ITMO University Russian Federation

ISBN: (纸本)9781450387354

Abstract—Graphical user interface adaptation becomes an increasingly time-consuming and resource-intensive task due to modern programs complexity and a big variety of information output devices. In this paper we propose a method for adapting a graphical user interface based on a person's workflow using a specific implementation of the interface. this method makes it possible to adapt the interface to the peculiarities of the user's workflow through optimization in the navigation area between program windows.

关键词： Graphical user interface abstract user adaptation machine learning user workflow

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Conventional machine learning Techniques with Features Engineering for Preventive Larynx Cancer Detection 5

Conventional Machine Learning Techniques with Features Engin...

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5th international conference on Advanced Technologies for signal and Image processing (ATSIP)

作者： Ben Aicha, Anis Univ Carthage Higher Sch Commun Tunis SUPCOM LR11TIC04 COSIM Res Lab Carthage Tunisia Fac Sci Bizerte FSB Bizerte Tunisia

ISBN: (纸本)9781728175133

Larynx cancer is developed from precancerous state. Some precancerous lesions such as Keratosis, Leukoplakia, Erythrolplakia, Papiloma virus, etc., can be transformed into a cancer if they are note treated in time. In this paper, we propose a non-intrusive technique to detect precancerous lesions at an earlier stage. Hence, these lesions can be treated as soon as possible. the idea is based on the analysis of the human voice in order to detect pertinent acoustic features able to discriminate pathological voices with precancerous lesions from normal ones. We have tested a large number of speech acoustic features. A feature engineering methodology leads us to choose the most pertinent features. To detect mentioned lesions, several classification techniques are tested. Experimental results show the validity of the idea.

关键词： Larynx cancer vocal fold conventional machine learning techniques features engineering

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Data Management and Visual Information processing using machine learning

Data Management and Visual Information Processing using Mach...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Arhath Kumar Shivani Joshi Shaik Vaseem Akram Joel Alanya-Beltran Mohammed Saleh Al Ansari Vikas Tripathi Department of MCA NMAM institute of Technology Nitte (Deemed to be University) Karnataka Department of computer Science & Engineering GL Bajaj Institute of Technology & Management Greater Noida Uttar Pradesh Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India Department of Electronic Universidad Tecnológica del Perú Perú Department of Chemical Engineering College of Engineering University of Bahrain Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

“machine learning (ML) ”-based large-scale data insights are the foundation of many contemporary data-driven technologies. ML systems offer ways to define and carry out certain ML workloads effectively and flexibly. Because of information-driven application highlights, information-driven responsibility elements, and framework designs affected by customary information the executives draw near, data the board is at the centre of numerous ML frameworks. Moreover, a ton of present-day information-driven arrangements are based on AI (ML)- based on enormous data bits of knowledge. A few ML occupations can be characterized and executed effectively and deftly utilizing ML frameworks. Data the executives are at the underpinning of numerous ML frameworks are reasonable to information-driven application qualities, information-driven responsibilities attributes, and framework models affected by old-style information the board techniques. Various ML clients with different ML lifecycle obligations and ML abilities are available in many Calculations. Information researchers are ML clients who have specialized information in ML and examination to control the information and make ML models for the business. the potential issues with data management that might arise in settings where machine learning procedures are used in the real world. Because we have first-hand experience with such huge pipelines, we can home in on issues relating to the interpretation of training data as well as its validation, cleaning, and enrichment. the objective of this article is to draw attention to these issues, establish links to previous efforts in the database area, and identify research questions that have not yet been solved.

关键词： Training Visualization Computer vision Technological innovation Biological system modeling Training data machine learning

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