基于简化版python+VGG+MiniGoogLeNet的智能43类交通标志识别-深度学习算法应用(含工程源码)+数据集+模型

[{"title":"（ 26 个子文件 32.13MB ） 基于简化版python+VGG+MiniGoogLeNet的智能43类交通标志识别-深度学习算法应用(含工程源码)+数据集+模型","children":[{"title":"项目13 基于CNN的交通标志识别","children":[{"title":"工程文件","children":[{"title":"Test.ipynb <span style='color:#111;'> 390.59KB </span>","children":null,"spread":false},{"title":"pyimagesearch","children":[{"title":"Net2.ipynb <span style='color:#111;'> 3.43KB </span>","children":null,"spread":false},{"title":"Net4.ipynb <span style='color:#111;'> 7.51KB </span>","children":null,"spread":false},{"title":"Net4.png <span style='color:#111;'> 156.13KB </span>","children":null,"spread":false},{"title":"Net2.png <span style='color:#111;'> 113.67KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"__init__.cpython-37.pyc <span style='color:#111;'> 153B </span>","children":null,"spread":false}],"spread":true},{"title":".ipynb_checkpoints","children":[{"title":"Net4-checkpoint.ipynb <span style='color:#111;'> 7.51KB </span>","children":null,"spread":false},{"title":"Net2-checkpoint.ipynb <span style='color:#111;'> 3.43KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"signnames1.csv <span style='color:#111;'> 1.54KB </span>","children":null,"spread":false},{"title":"MiniVGG-First.ipynb <span style='color:#111;'> 23.77KB </span>","children":null,"spread":false},{"title":"MiniVGG-Final.ipynb <span style='color:#111;'> 21.10KB </span>","children":null,"spread":false},{"title":"gtsrb-german-traffic-sign","children":null,"spread":false},{"title":"说明.txt <span style='color:#111;'> 834B </span>","children":null,"spread":false},{"title":"Ipynb_importer.py <span style='color:#111;'> 2.76KB </span>","children":null,"spread":false},{"title":"output","children":[{"title":"test5.png <span style='color:#111;'> 33.00KB </span>","children":null,"spread":false},{"title":"test4.png <span style='color:#111;'> 37.59KB </span>","children":null,"spread":false},{"title":"testmodel4.pb <span style='color:#111;'> 1.97MB </span>","children":null,"spread":false},{"title":"test2.png <span style='color:#111;'> 29.54KB </span>","children":null,"spread":false},{"title":"testmodel2.pb <span style='color:#111;'> 13.27MB </span>","children":null,"spread":false},{"title":"testmodel5.pb <span style='color:#111;'> 19.41MB </span>","children":null,"spread":false}],"spread":true},{"title":"MiniGoogLeNet-Final.ipynb <span style='color:#111;'> 25.19KB </span>","children":null,"spread":false},{"title":"signnames.csv <span style='color:#111;'> 1.02KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"Ipynb_importer.cpython-37.pyc <span style='color:#111;'> 2.52KB </span>","children":null,"spread":false}],"spread":true},{"title":".ipynb_checkpoints","children":[{"title":"MiniGoogLeNet-Final-checkpoint.ipynb <span style='color:#111;'> 23.03KB </span>","children":null,"spread":false},{"title":"MiniVGG-First-checkpoint.ipynb <span style='color:#111;'> 22.29KB </span>","children":null,"spread":false},{"title":"MiniVGG-Final-checkpoint.ipynb <span style='color:#111;'> 21.32KB </span>","children":null,"spread":false},{"title":"Test-checkpoint.ipynb <span style='color:#111;'> 390.59KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}],"spread":true}]