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| 1 | DLC‐1:a Rho GTPase‐activating protein and tumour suppressor显示文摘 | Marian E.Durkin Bao‐ZhuYuan XiaolingZhou Drazen B.Zimonjic Douglas R.Lowy Snorri S.Thorgeirsson Nicholas C.Popescu | 2007 | Journal of Cellular and Molecular Medicine2007，，5： | 1 |
| 2 | A voxel-based lidar method for estimating crown base height for deciduous and pine trees显示文摘 | Sorin C.Popescu Zhao Kaiguang | | 0，，： | 1 |
| 3 | DLC‐1:a Rho GTPase‐activating protein and tumour suppressor显示文摘 | Marian E.Durkin Bao‐ZhuYuan XiaolingZhou Drazen B.Zimonjic Douglas R.Lowy Snorri S.Thorgeirsson Nicholas C.Popescu | 2007 | Journal of Cellular and Molecular Medicine2007，，5： | 1 |
| 4 | Assessing the performance of YOLOv5 algorithm for detecting volunteer cotton plants in corn fields at three different growth stages显示文摘The feral or volunteer cotton(VC)plants when reach the pinhead squaring phase(5–6 leaf stage)can act as hosts for the boll weevil(Anthonomus grandis L.)pests.The Texas Boll Weevil Eradication Program(TBWEP)employs people to locate and eliminate VC plants growing by the side of roads or fields with rotation crops but the ones growing in the middle of fields remain undetected.In this paper,we demonstrate the application of computer vision(CV)algorithm based on You Only Look Once version 5(YOLOv5)for detecting VC plants growing in the middle of corn fields at three different growth stages(V3,V6 and VT)using unmanned aircraft systems(UAS)remote sensing imagery.All the four variants of YOLOv5(s,m,l,and x)were used and their performances were compared based on classification accuracy,mean average precision(mAP)and F1-score.It was found that YOLOv5s could detect VC plants with maximum classification accuracy of 98%and mAP of 96.3%at V6 stage of corn while YOLOv5s and YOLOv5m resulted in the lowest classification accuracy of 85%and YOLOv5m and YOLOv5l had the least mAP of 86.5%at VT stage on images of size 416×416 pixels.The developed CV algorithm has the potential to effectively detect and locate VC plants growing in the middle of corn fields as well as expedite the management aspects of TBWEP. | Pappu Kumar Yadav J.Alex Thomasson Stephen W.Searcy Robert G.Hardin Ulisses Braga-Neto Sorin C.Popescu Daniel E.Martin Roberto Rodriguez Karem Meza Juan Enciso Jorge Solórzano Diaz Tianyi Wang | 2022 | Artificial Intelligence in Agriculture2022，，1： | 0 |
| 5 | 高度多孔纳米结构纤维素纤维的溶液纺丝工艺显示文摘由纤维素生产纤维的常规生产方法,迄今已生产了具有致密微结构和极大长径比的材料。在此介绍的表面多孔的纤维是一种新型纤维状材料,为科学家和工程师提供了许多挑战和机会。由于纳米结构纤维的特性,它在工业产品,例如从过滤到类似药物释放载体的特殊产品的许多用途中具有很大潜力。通过采用溶胶凝胶方法,首次制成了表面多孔的纳米结构纤维素纤维。 | C.Hacker T.Gries C.Popescu L.Ratke 骆为林(译) 行兰(校) | 2009 | 国际纺织导报2009，37，8： | 0 |
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