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基于改进YOLOv10的血细胞检测算法
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作者 李晨露 牛嘉琦 +1 位作者 王莉 牛群峰 《现代电子技术》 北大核心 2025年第19期122-128,共7页
为解决因血细胞粘连和重叠而导致的识别准确率低、漏检较为严重的问题,提出一种基于YOLOv10的改进算法BSTM-YOLO。通过在主干网络引入Swin Transformer,加强网络对弱目标的发现与表征能力,提升血小板检测精度;颈部网络采用BiFPN,通过跨... 为解决因血细胞粘连和重叠而导致的识别准确率低、漏检较为严重的问题,提出一种基于YOLOv10的改进算法BSTM-YOLO。通过在主干网络引入Swin Transformer,加强网络对弱目标的发现与表征能力,提升血小板检测精度;颈部网络采用BiFPN,通过跨层级的融合机制增强特征表示能力,提取更为丰富的红细胞特征以提高目标检测性能;最后将C2f_MSBlock模块嵌入主干网格,使用分层特征融合策略和异构卷积核选择协议,在减少特征冗余的同时提高识别准确率。实验结果表明,改进后的BSTM-YOLO的平均精度均值(mAP)为93.1%,比原YOLOv10提高2.7%,参数量降低7%,GFLOPs降低3.7%,节省了计算资源,同时提高了识别准确率,满足了实际场景对血细胞检测的要求。 展开更多
关键词 血细胞检测 YOLOv10 bstm-YOLO Swin Transformer BiFPN MSBlock
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Effects of LaNiO_3 Interlayer on the Microstructures and Electrical Properties of Ba_(0.9)Sr_(0.1)Ti_(0.99)Mn_(0.01)O_3 Multilayer
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作者 洪学鹍 shao tan +4 位作者 shao xueyi wang tao 张德宝 liu yushen feng jinfu 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2016年第6期1280-1283,共4页
The aim of this work was to investigate the effects of low-resistivity interlayer on the physical properties of periodic Ba_(0.9)Sr_(0.1)Ti_(0.99)Mn_(0.01)O_3(BSTM) multilayers prepared by a chemical solutio... The aim of this work was to investigate the effects of low-resistivity interlayer on the physical properties of periodic Ba_(0.9)Sr_(0.1)Ti_(0.99)Mn_(0.01)O_3(BSTM) multilayers prepared by a chemical solution deposition method. A LaNiO_3(LNO) layer was inserted into the periodic BSTM multilayer artificially to form a sandwiched configuration of BSTM/LNO/BSTM. The capacitances at low frequencies(〈100 k Hz) of the sandwiched multilayer are significantly enhanced compared to that of the pure BSTM multilayer. The space charge accumulated at the LNO layer was proposed to explain the enhancement based on Maxwell-Wagner(M-W) model. However, LNO interlayer leads to an increase in the leakage current. A non-Ohmic conduction region is observed for BSTM/LNO/BSTM multilayer when the electric field exceeds 100 k V/cm. The results offer a new approach to achieve dielectric films with high dielectric constant. 展开更多
关键词 bstm multilayers LNO M-W model
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