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19篇 您的检索式:作者名="SMAIL R"
    题名 作者 年代 出处 被引量
1Information Theoretic Approximations for the M/G/1 Retrial Queue with Unreliable Server 显示文摘AISSANI A SMAIL R 2003The European Simulation and Modelling Conference2003,,:1
2Detecting mitochondrial permeability transition by eonfocal imaging of intact cells pinocytically loaded with caleein显示文摘Jones R A Smail A Wilson M R 2002Eur J Biochem2002,269,16:1
3Gut and liver: the organs responsible for increased nitric oxide production after trauma-hemor-rhage and resuscitation显示文摘 Catanla R A Wang P 1998Arch Surg1998,133,4:1
4Evaluation of a violence risk assessment system (the Alert System) for reducing violence in an acute hospital: a before and after study显示文摘Kling R N Yassi A Smailes E 2011Int J Nurs Stud2011,48,53:1
5A statistical analysis of the galaxy populations of distant luminous X-ray clusters显示文摘Smail I Edge A C Ellis R S 0,,:1
6Trespass on railroad rights - of - way 显示文摘Smailes J Ries R Raslear T 2007Research results2007,6,19:1
7Numerical and experimental study of spherical capsules packed bed latent heat storage system 显示文摘Smail K A R Henriquez J R 2002Apphed Thermal Engineering2002,19,:1
8Cervical lymph node tuberculosis: diagnosis and treatment显示文摘Zaatar R Biet A Smail A 2009Ann Otolaryngol Chit Cervicofac2009,126,56:1
9Information theoretic approximations for the M/G/1 retrial queue with unreliable server显示文摘Aissani A Smail R 2003The European Simulation and Modelling Confe-rence2003,,:1
10Comparison of radia- tion doses from multislice computed tomography coronary angi- ography and conventional diagnostic angiography显示文摘Coles D R Smail M A Negus I S 2006J Am Coil Cardio[2006,47,9:1
11Detecting mitochondrial permeability transition by confocal imaging of intact cells pinocytically loaded with calcein显示文摘JONES R A SMAIL A WILSON M R 2002Eur J Biochem2002,269,16:1
12Detecting mitochondrial permeability transition by confocal imaging of intact ceils pinocytically loaded with calcein显示文摘Jones R A Smail A Wilson M R 2002Eur J Biochem2002,269,:1
13Comparison of radiation doses from multislice computed tomography coronary angiogTaphy and conventional diagnostic angiography显示文摘Coles I)R Smail MA Negus IS 2006Joumal of the American College of Cardiology2006,47,9:1
14Hematoporphyrin derivative induced photosensitivity of mitochondrial succinate dehydrogenase and selected cytosolic enzymes of R3230AC mammary adenocarcinomas of rats显示文摘Hilf R Smail DB Murant RS 1984Cancer Res1984,44,:1
15Isolation of salmon pancreas disease virus (SPDV) in cell culture and its ability to protect against infection by the 'wild type' agent 显示文摘Lopez-Doriga M V Smail D A Smith R J 2001Fish & Shellfish Immunology2001,1,:1
16Cough strength, secretions and extubation outcome in bum patients who have passed a spontaneous breathing trial显示文摘Smailes ST McVicar AJ Martin R 2013Burns2013,39,2:1
17Cough strength, secretions and extubation outcome in bum patients who have passed a spontaneous breathing trial显示文摘Smailes ST Mcvicar A J Martin R 2013Bums2013,39,2:1
18Comparison of radiation doses from muhislice computed tomography coronary and conventional diagnostic angiography 显示文摘COLES D R SMAIL M A NEGUS I S 2006J Am Coll Cardiol2006,47,9:1
19A Novel Hybrid Model Based on Machine and Deep Learning Techniques for the Classification of Microalgae显示文摘Classification and monitoring of microalgae species in aquatic ecosystems are important for understanding population dynamics.However,manual classification of algae is a time-consuming method and requires a lot of effort with expertise due to the large number of families and genera in its classification.The recognition of microalgae species has become an increasingly important research area in image recognition in recent years.In this study,machine learning and deep learning methods were proposed to classify images of 12 different microalgae species in order to successfully classify algae cells.8 Different novel models(MobileNetV3Small-Lr,MobileNetV3Small-Rf,MobileNetV3Small-Xg,MobileNetV3Large-Lr,MobileNetV3Large-Rf,MobileNetV3Large-Xg,Mobile-NetV3Small-Improved and MobileNetV3Large-Improved)have been proposed to classify these microalgae species.Among these proposed model structures,the best classification accuracy rate was 92.22%and the loss rate was 0.72,obtained from the MobileNetV3Large-Improved model structure.In addition,as a result of the experimental results obtained,metrics such as the confusion matrix,which can meet the experts in the correct diagnosis of microalgae species,were also evaluated.This research may in the future open a new avenue for the development of a cost-effective,highly sensitive computer-based system for the use of image analysis and deep learning techniques for the identification and classification of different microalgae.Volkan Kaya İsmail Akgül Özge Zencir Tanır 2023Phyton-International Journal of Experimental Botany2023,92,9:0
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