Author Affiliations
Abstract
1 Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian 350116, P. R. China
2 Center for Computational Neuroscience, Flatiron Institute, New York 10010, USA
Neurons can be abstractly represented as skeletons due to the filament nature of neurites. With the rapid development of imaging and image analysis techniques, an increasing amount of neuron skeleton data is being produced. In some scientific studies, it is necessary to dissect the axons and dendrites, which is typically done manually and is both tedious and time-consuming. To automate this process, we have developed a method that relies solely on neuronal skeletons using Geometric Deep Learning (GDL). We demonstrate the effectiveness of this method using pyramidal neurons in mammalian brains, and the results are promising for its application in neuroscience studies.
Pyramidal neuron geometric deep learning neuron skeleton semantic segmentation point cloud Journal of Innovative Optical Health Sciences
2023, 16(6): 2340006
School of Science, China University of Geosciences, Beijing 100083, China
laser plasma energetic liquid carbon content Frontiers of Optoelectronics
2018, 11(3): 261–266
深圳大学光电工程学院光电子器件与系统(教育部/广东省)重点实验室, 广东 深圳 518060
提出一种利用高斯函数来表征基于扫描相机的时域荧光测量系统脉冲响应的方法,建立了数学模型,用以描述系统所采集到的时域荧光衰减曲线。用高斯函数对所建立的时域荧光寿命测量系统的脉冲响应函数进行拟合处理,拟合优度达到0.995以上;利用所建立的数学模型对标准荧光染料玫瑰红的测量数据进行拟合处理,拟合优度均值达到0.996以上,荧光寿命标准差仅有1.7 ps。实验表明,利用所建立的数学模型处理基于扫描相机的时域荧光寿命测量数据,具有良好的稳定性和准确性。这种方法提高了系统测量的精度,简化了解卷积运算,只要用多个高斯函数描述脉冲响应函数就可以用于其他时域荧光寿命分析及荧光寿命成像技术中。
测量 扫描相机 荧光寿命 最小二乘法 数据拟合 中国激光
2011, 38(s1): s108001
1 西安通信学院 光纤通信实验室,陕西 西安 710106
2 西安邮电学院 计算机系,陕西 西安 710106
文章从密集波分复用(DWDM)系统抵抗恶意侵扰的角度,分析了光放大段(OAS)中掺铒光纤放大器(EDFA)和OAS长度的配置对系统稳定性的影响,认为EDFA累积噪声会随着放大器的级数增加而呈线性增长 ,而且还会随着OAS损耗的增大而呈指数增长。系统的OAS数量和接收机灵敏度确定时,选择恰当的EDFA配置和OAS长度,可以达到提高系统稳定性的效果。
稳定性 恶意侵扰 大信号(HSP)侵扰 大噪声(HNP)侵扰 stability malicious attack High Signal Power (HSP) attack High Noise Power (HNP) attack
1 Lanzhou University, Lanzhou 730000, CHN
2 Beijing Mechanical Industry Institute, Beijing 100083, CHN
XPS Heterojunction Interface state Surface state
1 Beijing Mechanical Industry Institute, Beijing 100083, CHN
2 Lanzhou University, Lanzhou 730000, CHN
AlP/GaP Raman Spectrum Short-period Superlattice