机译:诸如卷积神经网络算法溺水中自动硅藻试验的数字全载图像分析
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Xuzhou Med Univ Dept Forens Med Xuzhou 221000 Jiangsu Peoples R China;
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Xi An Jiao Tong Univ Coll Forens Med Dept Forens Pathol Xian 710061 Shaanxi Peoples R China;
Second Mil Med Univ Eastern Hepatobiliary Surg Hosp Mol Oncol Lab Shanghai 200438 Peoples R;
Shanghai Univ Med &
Hlth Sci Dept Biochem &
Physiol Shanghai 201318 Peoples R China;
Inner Mongolia Med Univ Dept Forens Med Hohhot 010110 Inner Mongolia Peoples R China;
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Minist Justice Shanghai Forens Serv Platform Shanghai Key Lab Forens Med Acad Forens Sci;
Convolutional neural network; Artificial intelligence; Diatom examination; Drowning; Forensic pathology;
机译:诸如卷积神经网络算法溺水中自动硅藻试验的数字全载图像分析
机译:分析全连接神经网络在数字图像分类过程中的熟练程度。不同分类算法在卷积层高级图像特征上的基准测试
机译:分析数字图像分类过程中完全连接神经网络的熟练程度分析。不同分类算法的基准从卷积层的高级图像特征
机译:基于遗传算法和卷积网络的全病理组织学图像分析数字病理应用
机译:卷积神经网络的图像基础心血管建模的自动分割和不确定量化
机译:通过卷积神经网络进行全幻灯片组织病理学图像分析(HASHI)的高通量自适应采样:在浸润性乳腺癌检测中的应用
机译:分析数字图像分类过程中完全连接神经网络的熟练程度分析。不同分类算法的基准从卷积层的高级图像特征