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MobileNetV2-master

于 2021-04-23 发布
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下载积分: 1 下载次数: 3

代码说明:

说明:  实现图像分类,可完成对图像的多分类问题,效果较好(Realize image classification, can complete the multi-classification of images, the effect is better)

文件列表:

MobileNetV2-master, 0 , 2019-05-25
MobileNetV2-master\.gitignore, 1157 , 2019-05-25
MobileNetV2-master\LICENSE, 1062 , 2019-05-25
MobileNetV2-master\README.md, 2536 , 2019-05-25
MobileNetV2-master\data, 0 , 2019-05-25
MobileNetV2-master\data\convert.py, 932 , 2019-05-25
MobileNetV2-master\images, 0 , 2019-05-25
MobileNetV2-master\images\MobileNetv2.png, 1124602 , 2019-05-25
MobileNetV2-master\images\net.jpg, 33976 , 2019-05-25
MobileNetV2-master\images\stru.jpg, 71631 , 2019-05-25
MobileNetV2-master\mobilenet_v2.py, 6066 , 2019-05-25
MobileNetV2-master\model, 0 , 2019-05-25
MobileNetV2-master\model\hist.csv, 25576 , 2019-05-25
MobileNetV2-master\train.py, 4679 , 2019-05-25

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    2006-04-27 09:09:14下载
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    全变分去噪 J=tv(I,iter,dt,ep,lam,I0) 输入: I - 灰度图像, iter - 迭代次数 [1], dt - 时间步长 [0.2], ep - 提升参数epsilon [1], lam - 保真项 lambda [0], I0 - 输入噪声图像 [I0=I] ([]中的是缺省值)( 全变分去噪 J=tv(I,iter,dt,ep,lam,I0) 输入: I - 灰度图像, iter- 迭代次数 [1], dt - 时间步长 [0.2], ep - 提升参数epsilon [1], lam - 保真项 lambda [0], I0 - 输入噪声图像 [I0=I] ([]中的是缺省值))
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  • chedaoxain
    说明:  实现车道线检测,运用Hough变换的原理(For the process of lane line detection, this paper first searches for the edge points of the lane line, mainly including image graying, image filtering, image edge enhancement and image binarization. Then the lane line edge line is fitted. This paper uses the Hough transform to perform a straight line fitting.)
    2020-01-12 15:57:32下载
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    一个具备线,矩形,椭圆的画图程序,可以设置颜色,宽度,字体(One with lines, rectangles, ellipses drawing program, you can set the color, width, font)
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    奇异值分解等方法对噪声进行去噪,算法简单,清晰易懂(Singular value decomposition method to noise denoising algorithm is simple, clear and easy to understand)
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