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

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7th International conference on Information and Communication Technology for Intelligent systems, ICTIS 2023

7th International Conference on Information and Communicatio...

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7th International conference on Information and Communication Technology for Intelligent systems, ICTIS 2023

ISBN: (纸本)9789819940394

The proceedings contain 45 papers. The special focus in this conference is on . The topics include: Skin Cancer Recognition Using CNN, VGG16 and VGG19;diagnosis of Cardiovascular Disease Using Machine Learning algorithms and Feature Selection Method for Class Imbalance Problem;similarity Based Answer Evaluation in Academic Questions Using Natural Language processing Techniques;fake News Detection Using Machine Learning and Deep Learning Classifiers;survey on Pre-Owned Car Price Prediction Using Random Forest Algorithm;sentiment Analysis of Youtube Comment Section in Indian News Channels;deep Learning Framework for Speaker Verification Under Multi Sensor, Multi Lingual and Multi Session Conditions;DLLACC: Design of an Efficient Deep Learning Model for Identification of Lung Air Capacity in COPD Affected Patients;Content Based Document image Retrieval Using Computer Vision and AI Techniques;drowsiness Detection System;Monitor the Effectiveness of Cardiovascular Disease Illness Diagnostics Utilizing AI and Supervised Machine Learning Classifiers;architecture Based Classification for Intrusion Detection System Using Artificial Intelligence and Machine Learning Classifiers;a Novel Privacy-Centric Training Routine for Maintaining Accuracy in Traditional Machine Learning systems;outside the Closed World: On Using Machine Learning for Network Intrusion Detection;data Collection for a Machine Learning Model to Suggest Gujarati Recipes to Cardiac Patients Using Gujarati Food and Fruit with Nutritive Values;plant and Weed Seedlings Classification Using Deep Learning Techniques;a Comprehensive Review on Various Artificial Intelligence Based Techniques and Approaches for Cyber Security;applicability of Machine Learning for Personalized Medicine;I-LAA: An Education Chabot;A Comparison of Machine Learning Approaches for Forecasting Heart Disease with PCA Dimensionality Reduction.

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Fast image Stitching Based on ORB and MSAC Algorithm

Fast Image Stitching Based on ORB and MSAC Algorithm

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Advanced algorithms and Control Engineering (ICAACE), International conference on

作者： Su Yan Xin Wang Qingfeng Qin Xiaomei Liu School of Information Engineering Weifang Engineering Vocational College Weifang Qingzhou China Qizhuang Primary School Miaozi Town Qingzhou City Weifang Qingzhou China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

In order to solve the problem of slow image stitching, which cannot meet the requirements of real-time high-resolution image stitching, this paper proposes a fast image stitching method based on ORB (Oriented FAST and Rotated BRIEF) algorithm and MSAC (M-estimator Sample Consumption) algorithm. ORB algorithm matching speed is very fast, which can meet the real-time requirements of image stitching. First, this paper uses ORB algorithm to extract feature points; MSAC is an improvement of RANSAC algorithm, which can eliminate the pseudo matching point pairs in image stitching. Therefore, this paper optimizes the matching point pairs based on MSAC algorithm, removes the wrong matching point pairs, and then solves the image transformation matrix through the correct matching point pairs; Finally, bilinear interpolation fusion algorithm is used to eliminate visible seams and remove stitching traces. The experimental results show that the algorithm in this paper not only has obvious advantages in processing speed, but also has better quality of image stitching according to relevant evaluation indicators.

关键词： Interpolation image transformation Control engineering Fuses Feature extraction Real-time systems image stitching Optimization

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17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025

17th Asian Conference on Intelligent Information and Databas...

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17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025

ISBN: (纸本)9789819660070

The proceedings contain 29 papers. The special focus in this conference is on Intelligent Information and Database systems. The topics include: GAMER-Pong: Game Adjustment by Monitoring Emotional Response;Machine Learning algorithms Comparison for Hand sEMG-Recorded Movements Classification;boosting Face Super-Resolution and Identification with Knowledge Distillation and Frequency Domain Loss;improving Efficiency image Captioning by Using Attention Mechanism Combined with Knowledge Graph;integrating Topological Data Analysis and Deep Learning: A Case Study in Cardiovascular Disease Prediction at Thu Duc Hospital;boosting Lightweight Multi-branch Network by Integrating Segment, Skeleton, and Attribute Information;continuous Recognition of Mouth Patterns in Japanese Sign Language for Visual Communication;Towards an UAV Visual Navigation System Based on Map processing and Spatial Matching Techniques: A Literature Review;image Enhancement with Boosted Schrödinger Bridge;kernel-Level Energy-Efficient Neural Architecture Search for Tabular Dataset;estimation of Distribution algorithms with Overlapped Subpopulations;energy-Efficient Edge Query processing for Smart City Using Query Prediction;influence Maximization with Fairness Cost on Groups in Online Social Networks;TMMP: Efficient Continual Learning via Mixture of LoRA Experts and Top Maximum Magnitude Parameter Fusion;ADMEdge: Accelerating Edge Computing Through Co-design for Enhanced Data Mobility;the Recursive Scheme of Clustering;TOPSIS-Inspired Socio-cognitive Mutation Operator for Metaheuristics;feature-Based Drift Detection in Non-stationary Data Streams Using Multiple Classifiers: A Comprehensive Analysis;a Feature Transformation Technique for Improving Ensemble Learning systems;explainable Artificial Intelligence to Improve Interpretability in Predictive Mutation Testing;an Analysis of Class Imbalance Challenges in Predictive Mutation Testing;efficient Vietnamese Name Detection Using Highly Discriminative N-Gra

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Analysis of Decision Tree and Random Forest algorithms for Nutrient Deficiency Classification in Citrus Leaves through image processing

Analysis of Decision Tree and Random Forest Algorithms for N...

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International conference on Telecommunication systems, Services, and Applications (TSSA)

作者： Lia Kamelia Rin Rin Nurmalasari Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia

The research presents a hybrid approach to identify and categorise nutritional deficiency syndrome in citrus leaves using image processing and machine learning. The method includes processing images, segmenting images and extracting color-texture information. The Decision Tree and the Random Forest algorithms use various statistical measures for classification, including mean, skewness, variance, entropy, maximum probability, angular second moment, contrast, correlation, dissimilarity, energy, and homogeneity. The test results show a range of performance levels, with an accuracy of 80.28% being attained by utilising an 80:20 data ratio in the Decision Tree approach. The Random Forest method’s highest accuracy, 91.25%, was reached using an 80:20 ratio. In conclusion, the accuracy of the Random Forest approach regularly beats that of the Decision Tree method.

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Directions for Optimizing the Process of Obtaining and processing Thermograms Using a Mobile Application

Directions for Optimizing the Process of Obtaining and Proce...

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Electrical, Electronic and Information Sciences (eStream), Open conference of

作者： Iryna Kyrychenko Kostiantyn Nechvolod Vitaliy Makarov Iryna Gruzdo Department of Software Engineering Kharkiv National University Of Radio Electronics Kharkiv Ukraine Department of Surgery No.4 Kharkiv National Medical University Kharkiv Ukraine

ISBN: (数字)9798331598730

ISBN: (纸本)9798331598747

Thermography is an advanced diagnostic method widely used in various fields, including medicine, engineering, and industrial applications. With the increasing use of mobile applications in diagnostics, optimising thermographic analysis for mobile platforms has become a significant area of research. This paper examines the key aspects of thermographic imaging, including the principles of infrared radiation detection, image processing techniques, and integrating thermal data into mobile applications. Special attention is given to the challenges of mobile implementation, such as hardware limitations, real-time processing, and accuracy in temperature measurement. Additionally, the study explores potential solutions, including AIbased image enhancement, cloud-based computing, and optimised algorithms for efficient thermal data analysis. The findings highlight the importance of balancing computational efficiency with diagnostic accuracy to ensure the reliability and effectiveness of mobile thermography applications.

关键词： Optical filters image segmentation Accuracy Biomedical optical imaging Infrared imaging Optical variables measurement Optical imaging Mobile handsets Real-time systems Mobile applications

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Face Mask Detection Using Viola-Jones and Cascade Classifier

Face Mask Detection Using Viola-Jones and Cascade Classifier

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2022 International conference on Augmented Intelligence and Sustainable systems, ICAISS 2022

作者： Tasfia, Sheikh Reno, Saha Military Institute of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh Bangladesh Army International University of Science and Technology Department of Computer Science and Engineering Cumilla Bangladesh

ISBN: (纸本)9781665489621

Globally, the COVID-19 coronavirus outbreak is causing chaos in human health and therefore, the healthcare sector is in serious disarray. Many precautions have been taken to prevent the spread of this disease, including the usage of masks, which is strongly recommended by the World Health Organization (WHO). This research study has used the Viola-Jones algorithm for detecting face masks, where Histogram Equalization, Unsharp Filter and Gamma Correction are used as the preferred image pre-processing techniques to improve the overall accuracy. Haar Feature Selection is applied for creating integral images and AdaBoost training is performed on these images. Cascade classifier, a machine learning-based approach, is also integrated with the base algorithm where a cascade function assists Viola-Jones in accurately detecting objects in images. A total number of 1670 images is used in this work and our system is compared with four other machine learning algorithms, where Viola-Jones outperforms these ML-based classifiers and the overall accuracy obtained is 96%. © 2022 IEEE.

关键词： image enhancement

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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)9783031722837

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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A Comparative Review on image Analysis with Machine Learning for Extended Reality (XR) Applications 2nd

A Comparative Review on Image Analysis with Machine Learning...

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2nd International conference on Ubiquitous Computing and Intelligent Information systems (ICUIS)

作者： Vijayakumar, P. Dilliraj, E. SRM Inst Sci & Technol Chengalpattu Tamil Nadu India

ISBN: (纸本)9789811925412;9789811925405

Progressions in Medical, Industrial 4.0, and training require more client communication with the information in reality. Extended reality (XR) development could be conceptualized as a wise advancement and a capable data variety device fitting for far off trial and error in image processing. This innovation includes utilizing the Head Mounted Devices (HMD) built-in with a functionalities like data collection, portability and reproducibility. This article will help to understand the different methodologies that are used for 3Dimensional (3D) mode of interaction with the particular data set in industries to refine the system and uncovers the bugs in the machineries. To identify the critical medical issues, the future technology can give a comfort for the medic to diagnose it quickly. Educators currently utilizing video animation are an up-rising pattern. Important methods used for various applications like, Improved Scale Invariant Feature Transform (SIFT), Block Orthogonal Matching Pursuit (BOMP), Oriented fast and Rotated Brief (ORB) feature descriptor and Kanade-Lucas-Tomasi (KLT), Semi-Global Block Matching (SGBM) algorithm etc., In high-speed real time camera, the position recognition accuracy of an object is less than 65.2% as an average in motion due to more noise interferences in depth consistency. So, more optimization is needed in the algorithm of depth estimation. processing time of a target tracking system is high (10.670 s), that must be reduced to provide increased performance in motion tracking of an object in real-time. XR is a key innovation that is going to work with a change in perspective in the manner in which clients collaborate with information and has just barely as of late been perceived as a feasible answer for tackling numerous basic requirements.

关键词： 3D reconstruction Augmented reality (AR) Extended reality (XR) image depth analysis Machine learning algorithms Mixed reality (MR) Motion tracking Virtual reality (VR)

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U-Net-based COVID-19 CT image Semantic Segmentation: A Transfer Learning Approach 7

U-Net-based COVID-19 CT Image Semantic Segmentation: A Trans...

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7th International conference on image and Signal processing and their Applications, ISPA 2022

作者： Ferdi, Abdesselam Benierbah, Said Ferdi, Youcef Frères Mentouri Constantine 1 University Electronics Department Constantine Algeria National Higher School of Biotechnology Biotechnology Department Constantine Algeria

ISBN: (纸本)9781665480420

Deep learning (DL) algorithms are widely applied in many disciplines such as medical imaging, bioinformatics, and computer vision. DL models have been used in medical imaging to perform image segmentation, classification, and detection. During the outbreak of the COVID-19 pandemic, DL has been extensively used to develop COVID-19 screening systems. The reverse transcription-polymerase chain reaction (RT-PCR) is the gold standard method for COVID-19 screening. However, DL has been proposed to detect patients infected with COVID-19 through radiological imaging in Chest X-rays and chest computed tomography (CT) images. This paper proposes transfer learning to train modified U-Net models to segment the COVID-19 chest CT images into two regions of lung infection (ground-glass and consolidation). The proposed modified U-Net models were constructed by replacing the encoder part with a pre-trained convolutional neural network (CNN) model. Three pre-trained CNN models, namely, EfficientNet-b0, EfficientNet-b1, and EfficientNet-b2 were used. The proposed models were evaluated on the COVID-19 CT images Segmentation dataset available in an open Kaggle challenge. The obtained results show that the proposed EfficientNet-b2_U-Net model yielded the highest FScore of 0.5666. © 2022 IEEE.

关键词： COVID-19

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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)9789819736034

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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