搜索资源列表
Ncubicspline-P155-Q-28
- 在matlab中用自然边界条件画小狗， P155 Q 28，数值分析-Draw a dog by natural cubicspline interpolation in matlab, P155 Q 28， numeriacal analysis
liegouzhuituzi51
- 数学实验中用matlab对猎狗追逐兔子进行的仿真和分析-Matlab to the hunting dog chasing rabbits simulation
W10
- 一个小型的专家系统，关于判断狗的种类的专家系统-A small expert system, expert system to determine the type of dog
poor dog Matlab *.m file
- poor_dog.m funny! enjoy it!
tdl
- 在迅雷狗狗中打开连接,在点击下载前的页面把地址复制下来,然后粘贴到程序左边的方框中,点击运行按钮,就会把源地址转换出来(注意:带有"-"等特殊字符可能会转换有误,请自行处理,源码虽然简单,但是实用,希望能过)-Thunder Dog open connection before the Download page to copy down the address, and then paste it into the box to the left of the program, click o
sjsj
- 灵灵狗 V9电子狗的升级压缩包非常好用 免费升级-Lingling dog V9 electronic dog upgrade compressed package is very easy to use free upgrade
mfile
- Fuzzy Logic Control Example: Dog Chases Cat
light_preprocess
- 该代码是对人脸进行光照处理，先进行gamma变换，然后进行Dog双边滤波，然后进行灰度亮度的均衡。该方法能够有效提高光照变化的情况下的系统识别性能-The code is the human face of light treatment, the first for gamma conversion, and then Dog bilateral filtering, then the brightness of the gray balance. The method can effecti
tuzi
- 采用二分法原理，利用matlab来进行狗追兔子的仿真。-Using the principle of dichotomy, which can simulate the dog chased the rabbit by matlab.
SIFT
- sift算法实现与研究，包括gaussian，DOG尺度空间的构造，极值点的检测，边缘检测，计算方向，形成描述子，关键点的匹配-sift algorithm and Research
Word-Ladder
- 给定两个词(beginWord和endWord)和字典的单词列表,找到所有最短转换序列(s)beginWord endWord,这样: 一次只能改变一个字母；每个中间必须存在于词列表-Given two words (beginWord and endWord), and a dictionary s word list, find all shortest transformation sequence(s) beginWord to endWord, such that: Onl
PF 15.2.1
- U will see what up FFTD. dat dog meteials. is the one whom.
How to apply Difference of Gaussian(DoG)
- A Neutrosophic Image segmentation book
tensorflow实现猫狗识别
- 使用tensorflow 开源框架实现猫狗种类分类识别外框代码(Using tensorflow open source framework to realize cat dog classification and identification frame code)
imageRecognises
- Python编程Keras训练神经网络,识别猫狗图片(Python programming and Keras training neural network,recognition the cat or dog in the picture.)
pyDogVsCat
- 识别率85%，kaggle上有名的猫狗大战算法，可以很方便的查看分类结果。每一个epch需要22s左右（GTX1050Ti 4G）(The recognition rate is 85%. The famous dog and dog algorithm on kaggle is very convenient for us to see the classification results. Each epch needs about 22s (GTX1050Ti 4G))