产品详情
说明： 用CNN及MLP等方法识别minist数据集
(Recognition of Minist data sets by means of CNN and MLP)
(Recognition of Minist data sets by means of CNN and MLP)
文件列表：
MLP-CNN-Minst-Digital-Classifacation-master, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.gitignore, 7 , 2016-10-29
__MACOSX, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\._.gitignore, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\.idea, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\dictionaries, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\dictionaries\Sherry.xml, 85 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\inspectionProfiles, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\misc.xml, 196 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\MLP-CNN-Minst-Digital-Classifacation-master.iml, 455 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\modules.xml, 338 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\workspace.xml, 35414 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\layers.cpython-36.pyc, 4213 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\loss.cpython-36.pyc, 673 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\mnist.cpython-36.pyc, 1828 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\network.cpython-36.pyc, 1489 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\optimizer.cpython-36.pyc, 1006 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\solve_net.cpython-36.pyc, 1489 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\utils.cpython-36.pyc, 657 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\data, 0 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\t10k-images-idx3-ubyte, 7840016 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._t10k-images-idx3-ubyte, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\t10k-labels-idx1-ubyte, 10008 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._t10k-labels-idx1-ubyte, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\train-images-idx3-ubyte, 47040016 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._train-images-idx3-ubyte, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\train-labels-idx1-ubyte, 60008 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._train-labels-idx1-ubyte, 212 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._data, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\layers.py, 2528 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._layers.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\loss.py, 279 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._loss.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\mnist.py, 1855 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._mnist.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\network.py, 1448 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._network.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\optimizer.py, 965 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._optimizer.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\run_cnn.py, 1236 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._run_cnn.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\run_mlp.py, 872 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._run_mlp.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\solve_net.py, 2201 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\utils.py, 336 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\._codes, 212 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\MNIST Digits Classification with Theano (MLP %2B CNN).pdf, 75616 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\._MNIST Digits Classification with Theano (MLP %2B CNN).pdf, 212 , 2016-10-29
__MACOSX\._MLP-CNN-Minst-Digital-Classifacation-master, 212 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.gitignore, 7 , 2016-10-29
__MACOSX, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\._.gitignore, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\.idea, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\dictionaries, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\dictionaries\Sherry.xml, 85 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\inspectionProfiles, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\misc.xml, 196 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\MLP-CNN-Minst-Digital-Classifacation-master.iml, 455 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\modules.xml, 338 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\.idea\workspace.xml, 35414 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__, 0 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\layers.cpython-36.pyc, 4213 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\loss.cpython-36.pyc, 673 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\mnist.cpython-36.pyc, 1828 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\network.cpython-36.pyc, 1489 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\optimizer.cpython-36.pyc, 1006 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\solve_net.cpython-36.pyc, 1489 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\__pycache__\utils.cpython-36.pyc, 657 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\data, 0 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\t10k-images-idx3-ubyte, 7840016 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data, 0 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._t10k-images-idx3-ubyte, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\t10k-labels-idx1-ubyte, 10008 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._t10k-labels-idx1-ubyte, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\train-images-idx3-ubyte, 47040016 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._train-images-idx3-ubyte, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\data\train-labels-idx1-ubyte, 60008 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\data\._train-labels-idx1-ubyte, 212 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._data, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\layers.py, 2528 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._layers.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\loss.py, 279 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._loss.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\mnist.py, 1855 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._mnist.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\network.py, 1448 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._network.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\optimizer.py, 965 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._optimizer.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\run_cnn.py, 1236 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._run_cnn.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\run_mlp.py, 872 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\codes\._run_mlp.py, 212 , 2016-10-29
MLP-CNN-Minst-Digital-Classifacation-master\codes\solve_net.py, 2201 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\codes\utils.py, 336 , 2018-03-23
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\._codes, 212 , 2018-03-23
MLP-CNN-Minst-Digital-Classifacation-master\MNIST Digits Classification with Theano (MLP %2B CNN).pdf, 75616 , 2016-10-29
__MACOSX\MLP-CNN-Minst-Digital-Classifacation-master\._MNIST Digits Classification with Theano (MLP %2B CNN).pdf, 212 , 2016-10-29
__MACOSX\._MLP-CNN-Minst-Digital-Classifacation-master, 212 , 2018-03-23
