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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems IV"

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image Completion Via Dual-Path Cooperative Filtering

Image Completion Via Dual-Path Cooperative Filtering

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International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Pourya Shamsolmoali Masoumeh Zareapoor Eric Granger Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University China School of Automation Shanghai Jiao Tong University China Dept. of Systems Eng. Lab. d’Imagerie de Vision et d’Intelligence Artificielle ETS Canada

Given the recent advances with image-generating algorithms, deep image completion methods have made significant progress. However, state-of-art methods typically provide poor cross-scene generalization, and generated masked areas often contain blurry artifacts. Predictive filtering is a method for restoring images, which predicts the most effective kernels based on the input scene. Motivated by this approach, we address image completion as a filtering problem. Deep feature-level semantic filtering is introduced to fill in missing information, while preserving local structure and generating visually realistic content. In particular, a Dual-path Cooperative Filtering (DCF) model is proposed, where one path predicts dynamic kernels, and the other path extracts multi-level features by using Fast Fourier Convolution to yield semantically coherent reconstructions. Experiments on three challenging image completion datasets show that our proposed DCF outperforms state-of-art methods.

关键词： Filtering Semantics Signal processing algorithms Predictive models Feature extraction Prediction algorithms image restoration

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Comparative Study of Various Methods proposed to improve performance of 3D Graphics Pipeline 1

Comparative Study of Various Methods proposed to improve per...

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1st International conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Gothi, Ankita Anilkumar Kolhare, Neelima R. Kapse, Yogita D. College of Engineering Dept. of Electronics and Telecommunications Pune India

ISBN: (纸本)9798350342796

The majority of consumer electronics nowadays, including laptops and desktops, have integrated GPUs (iGPUs). Examples are AMD's APUs and Intel's HD or Iris Graphics. Real-time graphical rendering is the primary task performed by GPUs. These programs generate the corresponding image(s) from a description of a scene and rendered by evaluating the colors of each pixel in it. The attractive shading effects and green landscapes in current gaming engines demonstrate how close rendering of 3D graphics has gotten to true-to-life grade. It is evident that present-day 3D graphics APIs have their shortcomings and must be upgraded to satisfy the demands of modern consumers. Therefore, innovative algorithms, techniques, and approaches are emerging every day, each with an edge over the rest with distinct pros and cons. Here, various such techniques are compared based on multiple performance parameters along with shortcomings and strength of each approach. © 2023 IEEE.

关键词： 3D display 3D Graphics Pipeline Graphics processing Unit (GPU) Graphics Rendering multi-GPU systems Split Frame Rendering (SFR)

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Survey on CAD systems Improving MRI-Based Brain Tumor Classification with Advanced Segmentation and Feature Extraction Techniques

Survey on CAD Systems Improving MRI-Based Brain Tumor Classi...

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Computational Intelligence and Network systems (CINS), International conference on

作者： Sivapathi Arunachalam Prabaharan Lakshminarayanan School of Computing SASTRA Deemed University Thanjavur Tamil Nadu India

ISBN: (数字)9798331504106

ISBN: (纸本)9798331504113

Tumors are among the main causes of death not only in developed countries but also in developing ones. Cancerous neoplasms are a significant health problem in the world. Treatment, thus, calls for early diagnosis. Nearly one in six deaths is caused by cancer, which was approximately 10 million deaths in 2020 given by WHO. Actually, many cancers can be cured if treated effectively and early. In that regard, it presents the CAD system based on designing an automatic detector for detection and classification of brain tumors from MRI images. That is why methodologies, such as Support Vector Machine(SVM), Principal Component Analysis(PCA), Discrete Wavelet Transform and K-means clustering have been used in this paper. It predicts at two levels; first, differentiates between MRI images if they belong to either normal or abnormal types, and then differentiates the cancerous from noncancerous types. Apart from its promising results, there is not enough efficiency in the processing time, though. This paper looks towards noise reduction techniques and image segmentation and feature extraction methods for improving classification performance with the overcoming of limitations of current methods. Further on, advanced computational algorithms, such as the OFCM technique, are discussed to pinpoint more accurate identification of tumor regions. All the image processing and segmentation techniques above with identifying some open challenges have outlined the possible improvement for brain tumor detection systems.

关键词： image segmentation Accuracy Magnetic resonance imaging Noise reduction Brain tumors Feature extraction Wavelet analysis Discrete wavelet transforms Classification algorithms Cancer

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Implementation of a Camera Sensor for Helmet Detection in Two-Wheelers and Its Integration with the Electronic Control Unit (ECU)

Implementation of a Camera Sensor for Helmet Detection in Tw...

引用

IEEE Industrial Electronics and Applications conference (IEACon)

作者： Akul P Abhijna MB Dhruvi T Avlani Dept. of Computer Science and Engineering Global Academy of Technology

ISBN: (数字)9798350382976

ISBN: (纸本)9798350382983

The governing bodies set across different regions have several rules and regulations for the safety of motorcyclists, which they must adhere to. Accidents are undesirable events that result in injuries, or sometimes even worse, deaths. These accidents could be averted by wearing helmets while riding. The idea of integrating the output of the image processing algorithms with the ignition system stems from the increased fatality rate of motorcyclists on the road. Therefore, this project aims to reduce such accidents by using a camera tracker as a sensor, where it is further implemented with image processing hardware, such as the Raspberry Pi Camera Module, which runs image processing algorithm to determine if helmet is being worn by the rider or not. Furthermore, Raspberry Pi Camera Module is connected to the ECU using appropriate communication protocols, and the ECU sends outputs that control the ignition system. For the helmet detection, control logics on microcontroller are developed in a way to send signals to the ECU regarding helmet detection status. This project is focused on improving safety and reducing accidents.

关键词： Visualization Accuracy image processing Motorcycles Ignition Helmets Cameras Turning Real-time systems Accidents

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2nd International conference on Science, Engineering Management and Information Technology, SEMIT 2023

2nd International Conference on Science, Engineering Managem...

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2nd International conference on Science, Engineering Management and Information Technology, SEMIT 2023

ISBN: (纸本)9783031722868

The proceedings contain 46 papers. The special focus in this conference is on Science, Engineering Management and Information Technology. The topics include: Verification and Validation of Knowledge Engineering systems: A Life Cycle Framework;The Critical Factors of Success of Gamification in Digital Banking Services: Using Analytic Hierarchy Process (AHP) Approach;e-Shopping Sites Preference Analysis with Multi-criteria Decision-Making Methods;advancing Anemia Diagnosis: Harnessing Machine Learning Methods for Accurate Detection;monkeypox Detection with K-mer Using Machine Learning algorithms;cloud Computing Model for Handling Medical Big Data: A Mobile Hospital Pervasive Healthcare Application;Harnessing Advanced AI Techniques: An In-Depth Analysis of Machine Learning Models for Improved Diabetes Prediction;image processing in Toxicology: A Systematic Review;augmented Reality Immersive World with Hologram Special Effect in Early Childhood Education;improving the Visual Ergonomics of Computerised Workplaces Through the Use of Specialised Eye-Rest Software;a Diagnosis Model Based on Federated Learning for Lung Cancer Classification;Arrhythmia Detection from ECG Traces images Using Transfer Learning Approach;enhancing Traffic Flow Prediction in Urban Areas Through Deep Learning and Probe Information: A Comparative Study;an Approach to Multi-agent Deep Q-Network Optimization of Signal Control in Multi-intersection Road Environments to Enhance Urban Traffic Flow;blockchain-Driven Smart Contracts: An Overview of Application Areas and Gap Identification in Construction Management Literature;stochastic Optimization Methodology for Production Planning with Uncertain Demand and Lead Time Based on the Digital Twin;role of Top Management Commitment and Information Technology Investment in Digital Transformation;antecedents of Mobile Banking Apps Adoption Among Consumers in Ghana.

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Real Time Vehicle Collision Using Bounding Box Methodology with Alert System

Real Time Vehicle Collision Using Bounding Box Methodology w...

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Science, Technology, Engineering and Management (ICSTEM), International conference on

作者： Sri Ram Chandra Goud Bandi Vamsi Goud Bezawada Mercy Paul Selvan Viji Amutha Mary Mary Posonia Anto Praveena Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

This abstract discusses a bounding box methodology-based real-time vehicle disaster detection system that is combined with an alarm system. Effective crash detection systems are particularly essential now to keep safety a priority because of the growing number of cars on the road. The offered method efficiently traces and detects potential crashes by using bounding boxes to demonstrate the sizes and locations of vehicles. The system closely evaluates video feeds from smartly located cameras using image processing and computer vision algorithms; after, in order to proceed with immediate action to stop crashes, an alert system is deployed to notify impending accidents to both pedestrians and cars. By providing precise and momentary crash detection, the proposed technique intends to boost road safety by depreciating the chance of accidents.

关键词： Pedestrians image processing Disasters Alarm systems Real-time systems Road safety Automobiles

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2nd NIELIT's International conference on Communication, Electronics and Digital Technologies, NICEDT 2024

2nd NIELIT's International Conference on Communication, Elec...

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2nd NIELIT's International conference on Communication, Electronics and Digital Technologies, NICEDT 2024

ISBN: (纸本)9789819736003

The proceedings contain 79 papers. The special focus in this conference is on Communication, Electronics and Digital Technologies. The topics include: Design and Development of Parallel Beamformer Model for RTL Verification;early Detection of Oral Cancer Using image processing and Computational Techniques;loRa Enabled IoT Sensor Framework for Monitoring Urban Flood in Guwahati City;study and Implementation of Smart Positioner Prototype for Industrial Applications;tactile Internet: A Next Gen IoT Technology;a Deep Learning Approach for Hardware Trojan Detection in Netlist of Integrated Circuits with Graph Neural Networks;a Comparative Study of Jpeg and Similar Compression Standards for Wireless Communication;iot-Based Transport Monitoring System for Pharmaceutical Industry;non-intrusive Remote Apiculture Monitoring System;design and Analysis of Enhanced Bandwidth Slotted Logarithmic Spiral Patch Antenna for 5G Communication;IoT Based Real-Time Automatic Number Plate Detection Using OpenCV;prompt Engineering for the Automated Generation of Weaving Pattern;blood Disease Detection System Based on Haemogram Report Using Decision Tree Algorithm;Development of SPR Sensor-Based System for Copper Ion Detection in Water;generation of YuBraj Twist and YuBrajTwest Weaves;maintenance and Performance of Solar Water Pump in a Rural Agricultural Community: A Case Study;integrative Analysis of Cancer Gene Expression Using Bio-Inspired algorithms and Machine Learning: Identification of Key Genes;Potential of AI in Pharma: Bridge the Gap Between Data and Therapeutics;A PC-Based Ultrasound Color Doppler Performance Improvement Using Intel® IPPs;Deep Reach Centrality: An Innovative Network Centrality Metric Grounded in Distance and Degree, with Its Performance Analysis Applied to the SARS-CoV-2 Protein–protein Interaction Network.

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Smart Healthcare: A Logical Development of Medical image processing Based Sleep Apnea Disease Detection Using Elevated Neural Classification Principle

Smart Healthcare: A Logical Development of Medical Image Pro...

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Innovative Computing, Intelligent Communication and Smart Electrical systems (ICSES), International conference on

作者： Jagadeesh. P Radhamani. V T. Ravi G. Charulatha D.Y. Shahare Hamzeh J Aljawawdeh Department of Electronics and Communication Engineering Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering college Chennai Department of ECE Rajalakshmi Engineering College Chennai Department of ECE Sathyabama Institute of Science and Technology Chennai Department of Biomedical Engineering Selvam College of Technology Namakkal Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Department of Software Engineering faculty of information technology Zarqa University Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Entirely common sleep disorder is the dangerous wakefulness (Apnea) of breathing during snoring. In this study, we explore the possibility of how medical image processing can be useful and accurate method for sleep disordered breathing detection. The new approach named as Sleep Apnea Analyzing Strategy (SAAS) is firstly tested with the help of existing method namely image base Sleep Apnea Analyzer (ISAA) that use less number or data to be processed and hence running on portable device delivering results much faster than other available methods, both being cross-validated against each other. Sleep Apnea image-based Detector using Ephysiology - A new Algorithm (SAAS) We rely on sophisticated image processing techniques to extract relevant characteristics from medical images (such as x-rays, CT scans or MRIs) which are indicative of patterns typically associated with sleep apnea. The proposed methodology includes image preprocessing to improve the quality of images, feature extraction for quantification and characterization of all relevant information during OSA trials in GUI interface through well-known classification algorithms to classify patients with at least 20 de-saturations without sleep apnea. Our research aims to help in the creation of automatic diagnostic methods that will lead to early detection and treatment for sleep apnea. Our objective with this work is to provide a fair evaluation of the proposed technique in terms of sensitivity, specificity and accuracy through using a large dataset.

关键词： Accuracy Sensitivity Computational modeling Signal processing algorithms X-rays Signal processing Feature extraction Sleep apnea Biomedical image processing Medical diagnostic imaging

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Design and Implementation of image processing Based Lane Detection and Gradual Braking System 7

Design and Implementation of Image Processing Based Lane Det...

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7th International conference on Communication and Electronics systems, ICCES 2022

作者： Karthika, J. Arjun, N.M. Gauthaaman, P.R. Gokul, R. Gokularaja, R. Sri Krishna College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

In the vehicle industry, automatic systems are more commonly used enterprise in accordance with improving rider security, traveller comfort, decreasing traffic congestion and increasing strength efficiency. The goal of its job is centered on enhancing the automatic shaft help systems of motors, trying to emulate human conduct, however, correcting feasible ethnical errors, namely distractions, need for visibility, and epoch reaction. The proposed regulation may optimize the depth of braking in accordance with the available range in order to decrease the car speed after the manoeuvre, but it may also give precedence to the driver in conjunction with lane detection. A sequence of tests is conducted overseas within its assignment with an automobile equipped with sensors to grant actual-time statistics touching arrest system. The statistics presented in the time of potent assessments are done through the use of the photograph technology technique. This record makes this possible according to the characterization of the entire hitch conditions on the basis of applied pressure on the brake circuit. It is viable in imitation of calculation, so that it automatically helps in the actual scenario of driving manoeuvres. This bill of exchange also analyses lane tier demise alert systems, photo handling algorithms, and image segmentation methods. © 2022 IEEE.

关键词： Traffic congestion

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matRadiomics: From Biomedical image Visualization to Predictive Model Implementation 21st

matRadiomics: From Biomedical Image Visualization to Predict...

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21st International conference on image Analysis and processing (ICIAP)

作者： Pasini, Giovanni Bini, Fabiano Russo, Giorgio Marinozzi, Franco Stefano, Alessandro Natl Res Council IBFM CNR Inst Mol Bioimaging & Physiol I-90015 Cefalu Italy Sapienza Univ Rome Dept Mech & Aerosp Engn Eudossiana 18 I-00184 Rome Italy

ISBN: (纸本)9783031133213;9783031133206

The development of radiomics tools allows the extraction of quantitative features from medical images, thus enhancing the available information for clinicians. However, to date, these tools do not allow the user to complete the radiomics workflow by stopping at the feature extraction step. Therefore, a new software, namely matRadiomics, was developed as a user-friendly tool with the aim of allowing the user to carry out all the steps of a radiomics study. Using a single tool, i) biomedical images can be imported and inspected, ii) the target can be identified and segmented, iii) features can be extracted from the target, iv) reduced and selected, and v) used to build a predictive model using machine learning algorithms. As result, two different feature extractors can be chosen, a Matlab-based extractor, and the Pyradiomics extractor naturally integrated into matRadiomics. Extracted features can be selected using a hybrid descriptive-inferential method, while selected features can be used to train three different classifiers: Linear Discriminant Analysis, K-Nearest Neighbors, and Support Vector Machines. Models' validation is performed using K-Fold Cross Validation and K-Fold Stratified Cross Validation. Finally, the performance metrics of each model are shown in the graphical interface of matRadiomics. In conclusion, the result of this study was the development, implementation, and validation of an innovative and complete radiomics tool that accompanies the researcher throughout the whole radiomics workflow.

关键词： Radiomics Software package Machine learning image analysis PET MRI CT

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