/MNIST-classification

classification of MNIST using SVM, MLP and CNN

Primary LanguagePython

MNIST-classification

classification of MNIST using SVM, MLP and CNN


CNN Result

image-20230318224005300


1 image-20230318224108412 test_1 test_2 test_3 test_4 test_5 test_6 test_7 test_8 test_9 test_10 test_11
2 test_64 test_65 test_66 test_67 test_68 test_69 test_70 test_71 test_72 test_73 test_74 test_75
3 test_128 test_129 test_130 test_131 test_132 test_133 test_134 test_135 test_136 test_137 test_138 test_139
4 test_192 test_193 test_194 test_195 test_196 test_197 test_198 test_199 test_200 test_201 test_202 test_203
5 test_256 test_257 test_258 test_259 test_260 test_261 test_262 test_263 test_264 test_265 test_266 test_267

Epoch Train Accuracy Train Loss Val Accuracy
1 0.9017 0.3166 0.9533
2 0.9592 0.1339 0.9563
3 0.9673 0.1057 0.9679
4 0.9693 0.1009 0.9672
5 0.9721 0.0917 0.9725

DNN Result

Train Result image-20230402144324650
Accuracy graph over train dataset and test dataset image-20230402144458539

SVM Result

Train Result image-20230402144832563
Accuracy graph over train dataset and test dataset image-20230402144856519

GAN image generation

Net Iteration Result
GAN image-20230530142527172 image-20230530142501911
DCGAN image-20230530153213930 image-20230530154118617