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| 1 | Therapeutic Efficacy of Neurostimulation for Depression:Techniques, Current Modalities, and Future Challenges显示文摘Depression is the most prevalent debilitating mental illness; it is characterized as a disorder of mood,cognitive function, and neurovegetative function. About one in ten individuals experience depression at some stage of their lives. Antidepressant drugs are used to reduce the symptoms but relapse occurs in *20% of patients. However,alternate therapies like brain stimulation techniques have shown promising results in this regard. This review covers the brain stimulation techniques electroconvulsive therapy,transcranial direct current stimulation, repetitive transcranial magnetic stimulation, vagus nerve stimulation, and deep brain stimulation, which are used as alternatives to antidepressant drugs, and elucidates their research and clinical outcomes. | Hafsah Akhtar Faiza Bukhari Misbah Nazir Muhammad Nabeel Anwar Adeeb Shahzad | 2016 | Neuroscience Bulletin2016，32，1： | 8 |
| 2 | Optimization Based on Convergence Velocity and Reliability for Hydraulic Servo System显示文摘This article presents an optimal hybrid fuzzy proportion integral derivative(HFPID) controller based on combination of proportion integral derivative(PID) and fuzzy controllers,by which the parameters could be evaluated by global optimization either in convergence velocity or in convergence reliability.Focusing on the nonlinear factors of hydraulic servo system,this article takes advantage of PID and fuzzy logic controller integrated with scaling factors to acquire precise tracking performances.To further improve the performances,it provides new developed optimization with rapid convergence to attain reliable approach probability.Focusing on the performance indictors of evolutionary algorithm,this article presents a new technique to predict reliability of the optimization algorithm.Statistics authenticates the effectiveness and robustness of the optimization.Further,many simulation and experimental results indicate that the optimal HFPID could acquire perfect immunity against parametric uncertainties with external disturbance. | Muhammad Babar Nazir | 2009 | Chinese Journal of Aeronautics2009，22，4： | 5 |
| 3 | Changes in Nutrient-Homeostasis and Reserves Metabolism During Rice Seed Priming:Consequences for Seedling Emergence and Growth显示文摘In this study influence of different seed priming treatments on the nutrient-homeostasis and reserve metabolism during seedling emergence and growth of rice were determined. Seed priming treatments included pre-germination, hydropriming for 48 h, osmohardening with KCl and CaCl2, ascorbate priming and hardening. All treatments shortened the emergence time and enhanced the energy and index of seedling emergence. Seedlings from primed seeds had greater length, number of roots and fresh and dry mass than control. Among the treatments, CaCl2, ascorbate and KCl proved better in enhancing emergence and seedling growth. Seed priming changed the pattern of N and Ca2+ homeostasis both of the seeds and seedlings, which were associated to enhancing α-amylase activity and reducing sugars content. Positive correlations of seedling attributes with nutrient content suggested that as a result of seed priming, most of N and Ca2+ were partitioned to embryo, which enhanced seedling emergence and subsequent growth of rice seedlings. | Muhammad Farooq Shahzad M A Basra Abdul Wahid Nazir Ahmad | 2010 | Agricultural Sciences in China2010，9，2： | 4 |
| 4 | Factors influencing hybrid maize farmers' risk attitudes and their perceptions in Punjab Province,Pakistan显示文摘Hybrid maize farmers have to face diverse kinds of climate, biological, price and financial risks. Farmers' risk perceptions and risk attitudes are essential elements influencing farm operations and management decisions. However, this important issue has been overlooked in the contemporary studies and therefore there is a dearth of literature on this important issue. The present research is therefore, an attempt to fill this gap. This study aims to quantify hybrid maize farmers' perceptions of disastrous risks, their attitudes towards risk and to explore the impacts of various farm and farm household factors on farmers' risk attitudes and risk perceptions. The present study is conducted in four hybrid maize growing districts of Punjab Province, Pakistan, using cross-sectional data of 400 hybrid maize farmers. Risk matrix and equally likely certainty equivalent(ELCE) method are used to rank farmers' perceptions of four catastrophic risk sources including climate, biological, price and financial risks and to investigate farmers' risk aversion attitudes, respectively. Furthermore, probit regression is used to analyze the determinants affecting farmers' risk attitudes and risk perceptions. The results of the study showed that majority of farmers are risk averse in nature and perceive price, biological and climate to be potential sources of risks to their farm enterprise. In addition, analysis divulges that distance from farm to main market, off-farm income, location dummies for Sahiwal and Okara, age, maize farming experience, access to extension agent, significantly(either negatively or positively) influence farmers' risk attitudes and risk perceptions. The study delivers valuable insights for farmers, agricultural insurance sector, extension services researchers and agricultural policy makers about the local understanding of risks to hybrid maize crop in developing countries, like Pakistan, and have implications for research on farmers' adaptation to exposed risks. | Shoaib Akhtar LI Gu-cheng Raza Ullah Adnan Nazir Muhammad Amjed Iqbal Muhammad Haseeb Raza Nadeem Iqbal Muhammad Faisal | 2018 | Journal of Integrative Agriculture2018，17，6： | 3 |
| 5 | 三维黏性流体流动的传质和传热特性:Darcy定律的应用(英文)显示文摘应用非线性增厚表面的Darcy多孔介质变形,对饱和三维黏性磁流体的动力学特性进行了研究,对驻点附近的流动进行了分析。应用牛顿加热和可变导热系数表征了热传输特性。并采用一阶化学反应和变质量扩散率进行质量输运。通过适当的变换,将得到的控制方程进行转换(实现控制方程的转换)。用同伦技术计算了解析收敛级数解。根据图形数据讨论了参数的物理性质。用图示对阻力系数、Sherwood数和Nusselt数等相关参数进行说明。结果表明,共轭和构造的化学反应参数增强了温度和浓度的分布。 | Iffat JABEEN Muhammad FAROOQ Nazir A. MIR | 2019 | Journal of Central South University2019，26，5： | 2 |
| 6 | 生物入侵过程中的植物-土壤反馈:一种入侵植物的凋落物分解对其本地近缘植物的影响显示文摘植物入侵可通过正或负的植物-土壤反馈效应改变土壤的生物和非生物性质,从而影响入侵栖息地的土壤理化性质。许多入侵物种的凋落物分解可增加土壤养分,降低本地植物多样性,并导致进一步的植物入侵。关于入侵植物凋落物在不同土壤类型及深度分解及反馈效应的研究依然很少。本研究旨在明确入侵植物南美蟛蜞菊(Sphagneticola trilobata)凋落物在不同土壤类型和不同土壤深度条件下的分解情况及其对本地近缘植物蟛蜞菊(S.calendulacea)生理生长的影响。将装有南美蟛蜞菊凋落物的尼龙袋加入到不同深度(即0、2、4和6 cm)的砂土、营养土和粘土中,经6个月的分解后,回收凋落物袋并计算分解速率,随后在凋落物分解处理后的土壤中种植本地蟛蜞菊,并在生长期结束时测量其生理生态指标。研究结果表明,所有处理土壤类型中,凋落物在土壤深度为2和4 cm处分解后显著增加了土壤养分,而对本地蟛蜞菊的叶片叶绿素、叶氮含量等生长指标表现为负效应。因此,入侵植物南美蟛蜞菊凋落物分解对土壤养分表现为正的反馈效应,而对本地植物蟛蜞菊的生长表现为负效应。我们的研究结果还表明,入侵植物的凋落物分解对土壤和本地物种的影响还因凋落物分解所在的土壤深度而显著不同。未来的研究应侧重于入侵栖息地中更多本地和入侵物种的植物-土壤反馈效应,以及更多土壤类型和土壤深度的入侵植物凋落物效应。 | Jianfan Sun Susan Rutherford Muhammad Saif Ullah Ikram Ullah Qaiser Javed Ghulam Rasool Muhammad Ajmal Ahmad Azeem Muhammad Junaid Nazir Daolin Du | 2022 | Journal of Plant Ecology2022，15，3： | 2 |
| 7 | Maize production under risk:The simultaneous adoption of off-farm income diversification and agricultural credit to manage risk显示文摘Farmers in Pakistan continue to produce maize under various types of risks and adopt several strategies to manage those risks. This study is the first attempt to investigate the factors affecting the concurrent adoption of off-farm income diversification and agricultural credit which the farmers use to manage the risk to maize production. We apply bivariate and multinomial probit approaches to the primary data collected from four districts of Punjab Province in Pakistan. The results show that strong correlations exist between the off-farm diversification and agricultural credit which indicates that the use of one risk management strategy leads to another. The findings demonstrate that education, livestock number, maize farming experience, perceptions of biological risks and risk-averse nature of the growers significantly encourage the adoption of diversification as a risk management tool while farm size inversely affects the adoption of diversification. Similarly, in the adoption equation of credit, maize farming experience, farm size, perceptions of price and biological risks and risk attitude of farmers significantly enhance the chances of adopting agricultural credit to manage farm risks. These findings are important for the relevant stakeholders who seek to offer carefully designed risk minimizing options to the maize farmers. | Shoaib Akhtar LI Gu-cheng Adnan Nazir Amar Razzaq Raza Ullah Muhammad Faisal Muhammad Asad Ur Rehman Naseer Muhammad Haseeb Raza | 2019 | Journal of Integrative Agriculture2019，18，2： | 2 |
| 8 | Fine tuning of fuzzy rule-base system and rule set reduction using statistical analysis 显示文摘 | Muhammad Babar Nazir Shaoping Wang | 2011 | Journal Dynamic Systems Measurement and Control2011，133，4： | 1 |
| 9 | Can demography predict academic dishonest behaviors of students? a case of Pakistan 显示文摘 | Mian Sajid Nazir Muhammad Shakeel Aslam Muhammad Musarrat Nawaz | 2011 | International Education Studies2011，4，2： | 1 |
| 10 | Traffic Priority-Aware Medical Data Dissemination Scheme for IoT Based WBASN Healthcare Applications显示文摘Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human involvement.These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs.The BSNs generate critical data as it is related to patient’s health.The data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital signs.These data packets have different priority to deliver.The ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the patients.In this research,we propose a Traffic Priority-aware Medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the data.The assessment of the proposed scheme is carried out in various experiments.The simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes. | Muhammad Anwar Farhan Masud Rizwan Aslam Butt Sevia Mahdaliza Idrus Mohammad Nazir Ahmad Mohd Yazid Bajuri | 2022 | Computers, Materials & Continua2022，，6： | 1 |
| 11 | Cell walls digestion of ryegrass and Lucerne by cattle显示文摘 | Nazir A Muhammad A Abdur R | | 0，，02： | 1 |
| 12 | Impact of Accelerated Ultraviolet Weathering on Polymeric Composite Insulators Under High Voltage DC Stress显示文摘This study investigates the weatherability of room temperature vulcanized(RTV)silicone rubber(SiR)and epoxybased material specimens with a composition of different nano and micro fillers against the collegial effects of high voltage DC,UV and temperature stresses.Bulk power transmission over long distances via HVDC is considered an economic option these days,so to ensure the system reliability,it is also critical to investigate these insulators under DC stress along with other environmental stresses(especially UV and temperature).For experimentation,composite samples i.e.neat epoxy(NE),epoxy with 15%micro SiO_(2)(EMS),epoxy with 5%nano SiO_(2)(ENS),neat SiR(NS),SiR with 15%micro SiO_(2)(SMS)and SiR with 5%nano SiO_(2)(SNS)are fabricated and subjected to accelerated aging in a weather chamber for 3,360 hours.Results reveal that SMS and SNS offer better hydrophobic behavior followed by EMS.However noticeable surface discoloration in the form of whitish shade with minor blackish spots is found in the case of SMS,while remaining samples also showed considerable color fading.Scanning electron microscopy(SEM)and Fourier Transform Infrared Spectroscopy(FTIR)results showed that SNS and SMS presented quite excellent resistance to the exposure of fillers.Hardness and weight of all specimens are evaluated throughout the experiment and particularly for the water immersion test.Moreover,leakage current analysis indicated that SNS and SMS revealed high leakage current suppression compare to other samples.Findings indicate that SNS and SMS showed enhanced resistance against UV weathering under high voltage direct current stress. | Israr Ullah Muhammad Amin Haider Hussain M.Tariq Nazir | 2022 | CSEE Journal of Power and Energy Systems2022，8，3： | 1 |
| 13 | Study on the synthesis of spin labeled poly(styrene-co-maleic acid)s and their segmental motion显示文摘Study of the segmental mobility of polymer chains is important when the polymer is used as drag reduction agents of crude oil.Electron spin resonance(ESR)spectroscopy can provide important information about segmental dynamics of polymer chains,which is related to their microenvironment.In this article,we employed an amphiphilic polymer to study the effect of hydrophilic/hydrophobic balance of the polymers on the segmental motion of polymer chains.Poly(styrene-co-maleic acid)(PSMA)was spin labeled with 4-amino TEMPO radicals by increasing the concentration of radical moiety on the polymer chains.The PSMA and spin labeled-PSMAs(SL-PSMAs)were characterized by nuclear magnetic resonance(NMR),Fourier transform infrared(FT-IR)spectroscopy,Cyclic voltammetry(CV)and ESR techniques.Inter-polymer complexes(IPCs)of SL-PSMA-2 were prepared by employing polyethylene glycols(PEGs)of varying molecular weights.The results showed that the increased hydrophobic interactions of nitroxide radicals on the SLPSMAs’chains reduced the rotational mobility of spin labels and the random coil-toglobular transition of polymer chains occurred at higher pH value for SL-PSMAs,which showed a slow motion component in the ESR spectra of SL-PSMAs.Further,by increasing the molecular weight of PEGs in IPCs the complexation was increased,which also reduced the rotational motion of spin labels due to interpolymer hydrogen bonding causing a slow motion component in the ESR spectra.©2021 The Authors. | Kaleem-Ur-Rahman Naveed Li Wang Haojie Yu Qian Zhang Wei Xiong Raja Summe Ullah Ahsan Nazir Muhammad Usman Shah Fahad Amin Khan Md Alim Uddin Di Shen | 2022 | Magnetic Resonance Letters2022，2，2： | 1 |
| 14 | Accelerated ultraviolet weathering investigation on micro-/nano-SiO_(2)filled silicone rubber composites显示文摘This study attempts to elucidate whether the addition of micro and/or nano-silica(SiO_(2))particles can enhance the resistance of pure polydimethylsiloxane against synergistic effects of UV,temperature and high-voltage stress.Four types of composites(U-SR,M-SR,MN-SR and N-SR)are fabricated by adding micro and/or nano-silica particles and then subjected to multi-stress degradation in a test chamber.Results show that there is an apparent surface discoloration in the form of yellowish pale tint and a significant resistance to hydrophobicity reduction is offered by N-SR and MN-SR followed by M-SR and U-SR.Scanning electron microscopy and surface roughness findings proclaimed that N-SR and MN-SR offer excellent resistance against filler exposure and an increase in surface roughness.There is a minor reduction in absorbance level of Si(CH_(3))_(2) and Si-O-Si functional groups of composites but interestingly,hydrophilic hydroxyl group absorbance level is found higher in the U-SR comparatively.Furthermore,dielectric response measurements indicate considerable sensitivity to weathering with N-SR and MN-SR giving the lowest dielectric loss.Results indicate that the addition of nano-silica to pure and micro-silica filled SR can enhance its UV weathering resistance considerably by building an effective UV shielding layer. | Muhammad Tariq Nazir Bao Toan Phung | 2018 | High Voltage2018，3，4： | 1 |
| 15 | PIN diode modelling for simulation and development of high power limiter, digitally controlled phase shifter and high isolation SPDT switch显示文摘 | Nazir Muhammad Umair Kashif Muhammad Ahsan Naveed Malik Zahid Yaqoob | 2013 | International Bhurban Conference on Applied Sciences and Technology (IBCAST)2013，10，： | 1 |
| 16 | Photocatalysis vs adsorption by metal oxide nanoparticles显示文摘Background:Metal oxide(MO)nanomaterials and related nanocomposites have been extensively studied for their potential use in water treatment.Because of their controlled morphologies,texture qualities,variable surface chemistry,distinct crystalline nature,high stability,and tunable band edges,MO nanostructured materials are highly selective towards deleting organic contaminants and heavy metal ions via adsorption and semiconductor photocatalysis.Metal-enhanced photocatalysis has recently received increasing interest,mainly due to the ability of the metal to directly or indirectly degrade pollutants.A diverse selection of MOs,with titanium dioxide(Ti O2),zinc oxide(Zn O),iron oxides(IO),and tungsten(W),as well as graphene-MOs nanocomposites with variable structure,crystalline,and morphological properties,offers a powerful platform for the growth of effective catalysts.Methods:The current work discusses novel advancements and potential for the removal of adsorptive and photocatalytic degradation of organic compounds(phenolic,pesticide molecules,dyes,and so on)as well as heavy metal ions using semiconductor materials.A photocatalyst based on a MO-scheme heterostructure can manage the appropriate conduction band(CB)and valence band(VB)locations,securing considerable redox aptitude.This review should be of interest to the broad readership dealing with applied and fundamental aspects of water treatments and material sciences.Various strategies including surface modification,plasmonic enhancement,and metal cocatalysts have been introduced to enhance photocatalytic performance.Significant findings:The current article discussed the significantly utilized synthesis strategies and mechanism of heterojunction photocatalysts using a Z-scheme.Furthermore,adsorption sections guarantee that mercury,chromium,cadmium,arsenic,and lead-based ions are successfully removed from polluted water via the adsorption route.Numerous characteristics,such as concentration,coexisting ions,p H,and kind of chemical have converged to comprehend the adsorption procedure.The technological challenges and future approaches are discussed to maximize the photocatalytic and adsorption efficacy and the reusability of MO-based nanomaterials for water security. | Usman Qumar Jahan Zeb Hassan Rukhsar Ahmad Bhatti Ali Raza Ghazanfar Nazir Walid Nabgan Muhammad Ikram | 2022 | Journal of Materials Science & Technology2022，，36： | 1 |
| 17 | Novel Analysis of Two Kinds Hybrid Models in Ferro Martial Inserting Variable Lorentz Force Past a Heated Disk:An Implementation of Finite Element Method显示文摘In this article,the rheology of Ferro-fluid over an axisymmetric heated disc with a variable magnetic field by considering the dispersion of hybrid nanoparticles is considered.The flow is assumed to be produced by the stretching of a rotating heated disc.The contribution of variable thermophysical properties is taken to explore themomentum,mass and thermal transportation.The concept of boundary layermechanismis engaged to reduce the complex problem into a simpler one in the form of coupled partial differential equations system.The complex coupled PDEs are converted into highly nonlinear coupled ordinary differential equations system(ODEs)and the resulting nonlinear flow problem is handled numerically.The solution is obtained via finite element procedure(FEP)and convergence is established by conducting the grid-independent survey.The solution of converted dimensionless problem containing fluid velocity,temperature and concentration field is plotted against numerous involved emerging parameters and their impact is noted.From the obtained solution,it is monitored that higher values of magnetic parameter retard the fluid flow and escalating values of Eckert number results in to enhance temperature profile.Ferro-fluid flow and heat energy for the case of the Yamada Ota hybrid model are higher than for the case of the Hamilton Crosser hybrid model.Developing a model is applicable to the printing process,electronic devices,temperature measurements,engineering process and food-making process.The amount of mass species is reduced vs.incline impacts of chemical reaction and Schmidt parameter. | Enran Hou Umar Nazir Samaira Naz Muhammad Sohail Muhammad Nadeem Jung Rye Lee Choonkil Park Ahmed MGalal | 2023 | Computer Modeling in Engineering & Sciences2023，，5： | 1 |
| 18 | Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure显示文摘The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their space.Mainly brain tumour masses occur due to malignant masses.These tissues must die so that new tissues are allowed to be born and take their place.Tumour segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance variation.Manually finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and radiologists.Radiologists could not work for large volume images simultaneously,and many errors occurred due to overwhelming image analysis.The main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning approaches.This research study proposed an automatic model for tumor segmentation in MRI images.The proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics Technology Initiative(NIFTI)volumes into the 3D NumPy array.In the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated parameters.In the third step,the proposed model uses state-of-the-art Medical Image Computing and Computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour masses.Labelling of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and active.The proposed model is evaluated and gets the Dice Coefficient(DSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively. DSC value for the Low-gradeglioma (LGG) volumes for the test set is 0.9950, which shows the proposedmodel has achieved significant results in segmenting the tumour in MRI usingdeep learning approaches. The proposed model is fully automatic that canimplement in clinics where human experts consumemaximumtime to identifythe tumorous region of the brain MRI. The proposed model can help in a wayit can proceed rapidly by treating the tumor segmentation in MRI. | Muhammad Javaid Iqbal Muhammad Waseem Iqbal Muhammad Anwar Muhammad Murad Khan Abd Jabar Nazimi Mohammad Nazir Ahmad | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 19 | Gastrointestinal Diseases Classification Using Deep Transfer Learning and Features Optimization显示文摘Gastrointestinal diseases like ulcers, polyps’, and bleeding areincreasing rapidly in the world over the last decade. On average 0.7 millioncases are reported worldwide every year. The main cause of gastrointestinaldiseases is a Helicobacter Pylori (H. Pylori) bacterium that presents in morethan 50% of people around the globe. Many researchers have proposeddifferent methods for gastrointestinal disease using computer vision techniques.Few of them focused on the detection process and the rest of themperformed classification. The major challenges that they faced are the similarityof infected and healthy regions that misleads the correct classificationaccuracy. In this work, we proposed a technique based on Mask Recurrent-Convolutional Neural Network (R-CNN) and fine-tuned pre-trainedResNet-50 and ResNet-152 networks for feature extraction. Initially, the region ofinterest is detected using Mask R-CNN which is later utilized for the trainingof fine-tuned models through transfer learning. Features are extracted fromfine-tuned models that are later fused using a serial approach. Moreover, anImproved Ant Colony Optimization (ACO) algorithm has also opted for thebest feature selection from the fused feature vector. The best-selected featuresare finally classified using machine learning techniques. The experimentalprocess was conducted on the publicly available dataset and obtained animproved accuracy of 96.43%. In comparison with state-of-the-art techniques,it is observed that the proposed accuracy is improved. | Mousa Alhajlah Muhammad Nouman Noor Muhammad Nazir Awais Mahmood Imran Ashraf Tehmina Karamat | 2023 | Computers, Materials & Continua2023，，4： | 0 |
| 20 | Defocus blur detection using novel local directional mean patterns(LDMP)and segmentation via KNN matting显示文摘Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp regions that wrap significant information and require effective methods for information extraction.Existing defocus blur detection and segmentation methods have several limitations i.e.,discriminating sharp smooth and blurred smooth regions,low recognition rate in noisy images,and high computational cost without having any prior knowledge of images i.e.,blur degree and camera configuration.Hence,there exists a dire need to develop an effective method for defocus blur detection,and segmentation robust to the above-mentioned limitations.This paper presents a novel features descriptor local directional mean patterns(LDMP)for defocus blur detection and employ KNN matting over the detected LDMP-Trimap for the robust segmentation of sharp and blur regions.We argue/hypothesize that most of the image fields located in blurry regions have significantly less specific local patterns than those in the sharp regions,therefore,proposed LDMP features descriptor should reliably detect the defocus blurred regions.The fusion of LDMP features with KNN matting provides superior performance in terms of obtaining high-quality segmented regions in the image.Additionally,the proposed LDMP features descriptor is robust to noise and successfully detects defocus blur in high-dense noisy images.Experimental results on Shi and Zhao datasets demonstrate the effectiveness of the proposed method in terms of defocus blur detection.Evaluation and comparative analysis signify that our method achieves superior segmentation performance and low computational cost of 15 seconds. | Awais KHAN Aun IRTAZA Ali JAVED Tahira NAZIR Hafiz MALIK Khalid Mahmood MALIK Muhammad Ammar KHAN | 2022 | Frontiers of Computer Science2022，16，2： | 0 |
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