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您的检索式：作者名="Ismail Yasser"
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| 1 | C3-Modules显示文摘在如果每当 A 和 B 是 M 和 B=0 的直接被加数时,那么 B 是 M 的一个被加数,模块 M 被称为一个 C3 模块的地方, Utumi 在 self-injective 戒指上识别的连续性条件之一是 C3 条件。除了 injective 和 direct-injective 模块, C3 模块的班包括 semisimple,连续、不能分解、常规的模块。确实,每枚可交换的戒指是一枚 C3 戒指。在这份报纸,我们以 C3 条件提供模块的上述提及的班的一个一般、统一的处理,并且建立戒指的几个众所周知的班的新描述。 | Ismail Amin Yasser Ibrahim Mohamed Yousif | 2015 | Algebra Colloquium2015，22，4： | 11 |
| 2 | High-speed-Motion Estimation Architecture for Real-time Video Trans-mission显示文摘 | Goel Sumeer Ismail Yasser Bayoumi Magdy | 2012 | The Computer Journal2012，55，1： | 1 |
| 3 | Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management显示文摘Recently,autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare,agriculture,industrial automation,etc.Among the interesting applications of autonomous systems,their applicability in agricultural sector becomes significant.Autonomous unmanned aerial vehicles(UAVs)can be used for suitable site-specific weed management(SSWM)to improve crop productivity.In spite of substantial advancements in UAV based data collection systems,automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops.The recently developed deep learning(DL)models have exhibited effective performance in several data classification problems.In this aspect,this paper focuses on the design of autonomous UAVs with decision support system for weed management(AUAV-DSSWM)technique.The proposed AUAV-DSSWM technique intends to identify the weeds by the use of UAV images acquired from the target area.Besides,the AUAV-DSSWM technique primarily performs image acquisition and image pre-processing stages.Moreover,the Adam optimizer with You Only Look Once Object Detector-(YOLOv3)model is applied for the detection of weeds.For the effective classification of weeds and crops,the poor and rich optimization(PRO)algorithm with softmax layer is applied.The design of Adam optimizer and PRO algorithm for the parameter tuning process results in enhanced weed detection performance.A wide range of simulations take place on UAV images and the experimental results exhibit the promising performance of the AUAV-DSSWM technique over the other recent techniques with the accy of 99.23%. | Ashit Kumar Dutta Yasser Albagory Abdul Rahaman Wahab Sait Ismail Mohamed Keshta | 2022 | Computers, Materials & Continua2022，，10： | 0 |
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