5篇
您的检索式：作者名="Tayyab Imran"
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| 1 | RNA interference:The story of gene silencing in plants and humans显示文摘 | Mahmood-ur-Rahman Imran A Tayyab H | 2008 | Biotechnol Adv2008，26，3： | 1 |
| 2 | RNA interference: The story of gene silencing in plants and humans显示文摘 | Mahmood-ur-Rahman Imran Ali Tayyab Husnain Sheikh Riazuddin | 2008 | Biotechnology Advances2008，，3： | 1 |
| 3 | RNA interference:The story of gene silencing in plants and humans显示文摘 | Mahmood-ur-Rahman Imran Ali Tayyab Husnain | 2008 | Biotechnology Advances2008，26，： | 1 |
| 4 | Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space显示文摘Early detection of brain tumors is critical for effective treatment planning.Identifying tumors in their nascent stages can significantly enhance the chances of patient survival.While there are various types of brain tumors,each with unique characteristics and treatment protocols,tumors are often minuscule during their initial stages,making manual diagnosis challenging,time-consuming,and potentially ambiguous.Current techniques predominantly used in hospitals involve manual detection via MRI scans,which can be costly,error-prone,and time-intensive.An automated system for detecting brain tumors could be pivotal in identifying the disease in its earliest phases.This research applies several data augmentation techniques to enhance the dataset for diagnosis,including rotations of 90 and 180 degrees and inverting along vertical and horizontal axes.The CIELAB color space is employed for tumor image selection and ROI determination.Several deep learning models,such as DarkNet-53 and AlexNet,are applied to extract features from the fully connected layers,following the feature selection using entropy-coded Particle Swarm Optimization(PSO).The selected features are further processed through multiple SVM kernels for classification.This study furthers medical imaging with its automated approach to brain tumor detection,significantly minimizing the time and cost of a manual diagnosis.Our method heightens the possibilities of an earlier tumor identification,creating an avenue for more successful treatment planning and better overall patient outcomes. | Mudassir Khalil Muhammad Imran Sharif Ahmed Naeem Muhammad Umar Chaudhry Hafiz Tayyab Rauf Adham E.Ragab | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 5 | Ultrashort pulse capability at the L2I high intensity laser facility显示文摘The Laboratory for Intense Lasers(L2I) is a research centre in optics and lasers dedicated to experimental research in high intensity laser science and technology and laser plasma interaction. Currently the laboratory is undergoing an upgrade with the goal of increasing the versatility of the laser systems available to the users, as well as increasing the pulse repetition rate. In this paper we review the current status of the laser research and development programme of this facility, namely the upgraded capability and the recent progress towards the installation of an ultrashort, diode-pumped OPCPA laser system. | Gonqalo Figueira Joana Alves Joao M.Dias Marta Fajardo Nuno Gomes Victor Hariton Tayyab Imran Celso P.Joao Jayanath Koliyadu Swen Kunzel Nelson C.Lopes Hugo Pires Filipe Ruao Gareth Williams | 2017 | High Power Laser Science and Engineering2017，5，1： | 0 |
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