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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： asifa mehmood qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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Intelligent Traffic Surveillance through Multi-Label Semantic Segmentation and Filter-Based Tracking

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Computers, Materials & Continua 2023年第9期76卷 3707-3725页

作者： asifa mehmood qureshi Nouf Abdullah Almujally Saud S.Alotaibi Mohammed Hamad Alatiyyah Jeongmin Park Department of Creative Technologies Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Information Systems Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Engineering Tech University of KoreaSiheung-siGyeonggi-do15073Korea

Road congestion,air pollution,and accident rates have all increased as a result of rising traffic density andworldwide population *** the past ten years,the total number of automobiles has increased significantly over the *** this paper,a novel method for intelligent traffic surveillance is *** proposed model is based on multilabel semantic segmentation using a random forest classifier which classifies the images into five *** improve the results,mean-shift clustering was applied to the segmented ***,the pixels given the label for the vehicle were extracted and blob detection was applied to mark each *** the validation of each detection,a vehicle verification method based on the structural similarity index is *** tracking of vehicles across the image frames is done using the Identifier(ID)assignment technique and particle ***,vehicle counting in each frame along with trajectory estimation was done for each *** proposed system demonstrated a remarkable vehicle detection rate of 0.83 over Vehicle Aerial Imaging from Drone(VAID),0.86 over AU-AIR,and 0.75 over the Unmanned Aerial Vehicle Benchmark Object Detection and Tracking(UAVDT)dataset during the experimental *** proposed system can be used for several purposes,such as vehicle identification in traffic,traffic density estimation at intersections,and traffic congestion sensing on a road.

关键词： Traffic surveillance multi-label segmentation random forest particle filter computer vision

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Semantic Segmentation and YOLO Detector over Aerial Vehicle Images

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Computers, Materials & Continua 2024年第8期80卷 3315-3332页

作者： asifa mehmood qureshi Abdul Haleem Butt Abdulwahab Alazeb Naif Al Mudawi Mohammad Alonazi Nouf Abdullah Almujally Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Cognitive Systems Lab University of BremenBremen28359Germany

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway ***,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall *** learning is considered to be an efficient method for object detection in vision-based *** this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation *** model consists of six *** the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the *** pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in *** detection was exposed to Speeded Up Robust Feature(SURF)feature extraction to track multiple *** on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching ***,we implemented a Kalman filter to track multiple *** the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking *** experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art *** proposed implemented system provided 94.1%detection precision for Roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

关键词： Semantic segmentation YOLOv5 vehicle detection and tracking Kalman filter SURF

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Synthetic data as an investigative tool in hypertension and renal diseases research

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World Journal of Methodology 2025年第1期15卷 9-13页

作者： Aleena Jamal Som Singh Fawad qureshi Sidney Kimmel Medical College Thomas Jefferson UniversityPhiladelphiaPA 19107United States School of Medicine University of Missouri Kansas CityKansasMO 64106United States Division of Nephrology and Hypertension Mayo ClinicRochesterMN 55905United States

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in *** nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient *** is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension ***,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

关键词： Synthetic data Artificial intelligence Nephrology Blood pressure Research Editorial

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A New Attempt to Neutrosophic Soft Bi-Topological Spaces

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Computer Modeling in Engineering & Sciences 2022年第3期130卷 1565-1585页

作者： Arif mehmood Muhammad Aslam Muhammad Imran Khan Humera qureshi Choonkil Park Jung Rye Lee Department of Mathematics&Statistics Riphah International UniversitySector I-14Islamabad44000Pakistan Department of Mathematics College of SciencesKing Khalid UniversityAbha61413Saudi Arabia Department of Pure and Applied Mathematics(Statistics) University of HaripurHaripur22630Pakistan Research Institute for Natural Sciences Hanyang UniversitySeoul04763Korea Department of Data Science Daejin UniversityKyunggi11159Korea

In this article,new generalized neutrosophic soft∗b open set is introduced in neutrosophic soft bi-topological structurers(NSBTS)concerning soft points of the *** new set is produced by making the marriage of soft semi-open set with soft pre-open set in neutrosophic soft topological *** ample of results are investigated in NSBTS on the basis of this new neutrosophic soft∗b open *** examples are settled for justification of these *** non-validity of some results is vindicated with examples.

关键词： Neutrosophic soft set(NSS) neutrosophic soft points(NSP) neutrosophic soft bi-topological structurers(NSBTS) neutrosophic soft∗b-open set and neutrosophic soft∗b-separation axioms

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Triangular code:Near-optimal linear time fountain code

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Digital Communications and Networks 2023年第4期9卷 869-878页

作者： Jalaluddin qureshi Chuan Heng Foh Openbet North America MontrealCanada GIC&6GIC Institute for Communication Systems(ICS)University of SurreyGuildfordUnited Kingdom

In this paper,we propose Triangular Code(TC),a new class of fountain code with near-zero redundancy and linear encoding and decoding computational complexities of OeLklog kT,where k is the packet batch size and L is the packet data *** from previous works where the optimal performance of codes has been shown under asymptotic assumption,TC enjoys near-zero redundancy even under non-asymptotic settings for smallmoderate number of *** features make TC suitable for practical implementation in batteryconstrained devices in IoT,D2D and M2M network paradigms to achieve scalable reliability,and minimize latency due to its low decoding *** is a non-linear code,which is encoded using the simple shift and XOR addition operations,and decoded using the simple back-substitution *** it is nonlinear code at the packet level,it remains linear code when atomized at the bit *** use this property to show that the backsubstitution decoder of TC is equivalent to the Belief Propagation(BP)decoder of LT ***,TC can benefit from rich prolific literature published on LT code,to design efficient code for various *** the equivalency between the decoders of TC and LT code,we show that compared to state-of-the-art optimized LT code,TC reduces the redundancy of LT code by 68%-99% for k reaching 1024.

关键词： LT code Decoder Computational complexity Green computing Network coding

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Indispensable Hibi Relations and Grobner Bases

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Algebra Colloquium 2015年第4期22卷 567-580页

作者： Ayesha Asloob qureshi ] Abdus Salam School of Mathematical Sciences GC University Lahore. 68-B New Muslim "Ibwn Lahore 54600 Pakistan

In this paper we consider Hibi rings and Rees rings attached to a poset. We classify the ideal lattices of posets whose Hibi relations are indispensable and the ideal lattices of posets whose Hibi relations form a quadratic Grobner basis with respect to the rank lexicographic order. Similar classifications are obtained for Rees rings of Hibi ideals.

关键词： Hibi rings Hibi relations Gr5bner bases lattices

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A pulse shape discrimination of CsI(Tl) crystal with ~6He beam

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Nuclear Science and Techniques 2010年第1期21卷 35-38页

作者： FAISAL Jamil-qureshi School of Physics and State Key Laboratory of Nuclear Physics and Technology Peking University

The performance test of a CsI(Tl) crystal (70×27×23 mm3) was performed by applying the pulse shape discrimination technique for identification of light charged particles .The crystal is coupled to a photomultiplier tube during an experiment with 6He *** pulse waveform is fully recorded by employing a high precision digital *** fast and slow gates are used for the pulse shape discrimination and the best values for the gate widths were determined to be 0.5 μs and 1.67 μs,*** 6He,4He and 3He are successfully discriminated with this technique.

关键词：脉冲形状甄别次级束流晶体 CsI TI 识别技术光电倍增管数字示波器

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Fuzzy-Based Automatic Epileptic Seizure Detection Framework

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Computers, Materials & Continua 2022年第3期70卷 5601-5630页

作者： Aayesha Muhammad Bilal qureshi Muhammad Afzaal Muhammad Shuaib qureshi Jeonghwan Gwak Shaheed Zulfikar Ali Bhutto Institute of Science and Technology IslamabadPakistan Department of Computer Science&IT University of Lakki MarwatKPKPakistan Stockholm University StockholmSweden Department of Computer Science School of Arts and SciencesUniversity of Central AsiaKyrgyz Republic Department of Software Korea National University of TransportationChungju27469Korea Department of Biomedical Engineering Korea National University of TransportationChungju27469Korea Department of AI Robotics Engineering Korea National University of TransportationChungju27469Korea Department of IT&Energy Convergence(BK21 FOUR) Korea National University of TransportationChungju27469Korea

Detection of epileptic seizures on the basis of Electroencephalogram(EEG)recordings is a challenging task due to the complex,non-stationary and non-linear nature of these biomedical *** the existing literature,a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning *** characterizing features of epileptic and non-epileptic EEG signals overlap;therefore,it requires that analysis of signals must be performed from diverse *** studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG *** pose the challenge mentioned above,in this paper,a fuzzy-based epileptic seizure detection model is proposed that incorporates a novel feature extraction and selection method along with fuzzy *** proposed work extracts pattern features along with time-domain,frequencydomain,and non-linear analysis of *** applies a feature selection strategy on extracted features to get more discriminating features that build fuzzy machine learning classifiers for the detection of epileptic *** empirical evaluation of the proposed model was conducted on the benchmark Bonn EEG *** shows significant accuracy of 98%to 100%for normal *** classification cases while for three class classification of normal ***-ictal *** accuracy reaches to above 97.5%.The obtained results for ten classification cases(including normal,seizure or ictal,and seizure-free or inter-ictal classes)prove the superior performance of proposed work as compared to other state-of-the-art counterparts.

关键词： Medical image processing electroencephalography machine learning fuzzy system models seizure detection epileptic seizure virtualization

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Adaptive step-size modified fractional least mean square algorithm for chaotic time series prediction

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Chinese Physics B 2014年第5期23卷 129-137页

作者： BilalShoaib Ijaz Mansoor qureshi Shafqatullah Ihsanulhaq Department of Electronic Engineering Faculty of Engineering and Technology International Islamic University Islamabad Pakistan Department of Electrical Engineering AIR University Islamabad Pakistan School of Engineering and Applied Sciences ISRA University Islamabad Pakistan

This paper presents an adaptive step-size modified fractional least mean square （AMFLMS） algorithm to deal with a nonlinear time series prediction. Here we incorporate adaptive gain parameters in the weight adaptation equation of the original MFLMS algorithm and also introduce a mechanism to adjust the order of the fractional derivative adaptively through a gradient-based approach. This approach permits an interesting achievement towards the performance of the filter in terms of handling nonlinear problems and it achieves less computational burden by avoiding the manual selection of adjustable parameters. We call this new algorithm the AMFLMS algorithm. The predictive performance for the nonlinear chaotic Mackey Glass and Lorenz time series was observed and evaluated using the classical LMS, Kernel LMS, MFLMS, and the AMFLMS filters. The simulation results for the Mackey glass time series, both without and with noise, confirm an improvement in terms of mean square error for the proposed algorithm. Its performance is also validated through the prediction of complex Lorenz series.

关键词： fractional LMS kernel LMS Reimann-Lioville derivative Mackey glass and Lorenz time series

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