1. 程式人生 > >Deep Learning 33:讀論文“Densely Connected Convolutional Networks”-------DenseNet 簡單理解

Deep Learning 33:讀論文“Densely Connected Convolutional Networks”-------DenseNet 簡單理解

  1 Model created
  2 ____________________________________________________________________________________________________
  3 Layer (type) Output Shape Param # Connected to 
  4 ====================================================================================================
  5 input_1 (InputLayer) (None, 32
, 32, 3) 0 6 ____________________________________________________________________________________________________ 7 initial_conv2D (Convolution2D) (None, 32, 32, 24) 648 input_1[0][0] 8 ____________________________________________________________________________________________________ 9 batchnormalization_1 (BatchNorma (None, 32
, 32, 24) 96 initial_conv2D[0][0] 10 ____________________________________________________________________________________________________ 11 activation_1 (Activation) (None, 32, 32, 24) 0 batchnormalization_1[0][0] 12 ____________________________________________________________________________________________________
13 convolution2d_1 (Convolution2D) (None, 32, 32, 48) 1152 activation_1[0][0] 14 ____________________________________________________________________________________________________ 15 batchnormalization_2 (BatchNorma (None, 32, 32, 48) 192 convolution2d_1[0][0] 16 ____________________________________________________________________________________________________ 17 activation_2 (Activation) (None, 32, 32, 48) 0 batchnormalization_2[0][0] 18 ____________________________________________________________________________________________________ 19 convolution2d_2 (Convolution2D) (None, 32, 32, 12) 5184 activation_2[0][0] 20 ____________________________________________________________________________________________________ 21 merge_1 (Merge) (None, 32, 32, 36) 0 initial_conv2D[0][0] 22 convolution2d_2[0][0] 23 ____________________________________________________________________________________________________ 24 batchnormalization_3 (BatchNorma (None, 32, 32, 36) 144 merge_1[0][0] 25 ____________________________________________________________________________________________________ 26 activation_3 (Activation) (None, 32, 32, 36) 0 batchnormalization_3[0][0] 27 ____________________________________________________________________________________________________ 28 convolution2d_3 (Convolution2D) (None, 32, 32, 48) 1728 activation_3[0][0] 29 ____________________________________________________________________________________________________ 30 batchnormalization_4 (BatchNorma (None, 32, 32, 48) 192 convolution2d_3[0][0] 31 ____________________________________________________________________________________________________ 32 activation_4 (Activation) (None, 32, 32, 48) 0 batchnormalization_4[0][0] 33 ____________________________________________________________________________________________________ 34 convolution2d_4 (Convolution2D) (None, 32, 32, 12) 5184 activation_4[0][0] 35 ____________________________________________________________________________________________________ 36 merge_2 (Merge) (None, 32, 32, 48) 0 initial_conv2D[0][0] 37 convolution2d_2[0][0] 38 convolution2d_4[0][0] 39 ____________________________________________________________________________________________________ 40 batchnormalization_5 (BatchNorma (None, 32, 32, 48) 192 merge_2[0][0] 41 ____________________________________________________________________________________________________ 42 activation_5 (Activation) (None, 32, 32, 48) 0 batchnormalization_5[0][0] 43 ____________________________________________________________________________________________________ 44 convolution2d_5 (Convolution2D) (None, 32, 32, 48) 2304 activation_5[0][0] 45 ____________________________________________________________________________________________________ 46 batchnormalization_6 (BatchNorma (None, 32, 32, 48) 192 convolution2d_5[0][0] 47 ____________________________________________________________________________________________________ 48 activation_6 (Activation) (None, 32, 32, 48) 0 batchnormalization_6[0][0] 49 ____________________________________________________________________________________________________ 50 convolution2d_6 (Convolution2D) (None, 32, 32, 12) 5184 activation_6[0][0] 51 ____________________________________________________________________________________________________ 52 merge_3 (Merge) (None, 32, 32, 60) 0 initial_conv2D[0][0] 53 convolution2d_2[0][0] 54 convolution2d_4[0][0] 55 convolution2d_6[0][0] 56 ____________________________________________________________________________________________________ 57 batchnormalization_7 (BatchNorma (None, 32, 32, 60) 240 merge_3[0][0] 58 ____________________________________________________________________________________________________ 59 activation_7 (Activation) (None, 32, 32, 60) 0 batchnormalization_7[0][0] 60 ____________________________________________________________________________________________________ 61 convolution2d_7 (Convolution2D) (None, 32, 32, 48) 2880 activation_7[0][0] 62 ____________________________________________________________________________________________________ 63 batchnormalization_8 (BatchNorma (None, 32, 32, 48) 192 convolution2d_7[0][0] 64 ____________________________________________________________________________________________________ 65 activation_8 (Activation) (None, 32, 32, 48) 0 batchnormalization_8[0][0] 66 ____________________________________________________________________________________________________ 67 convolution2d_8 (Convolution2D) (None, 32, 32, 12) 5184 activation_8[0][0] 68 ____________________________________________________________________________________________________ 69 merge_4 (Merge) (None, 32, 32, 72) 0 initial_conv2D[0][0] 70 convolution2d_2[0][0] 71 convolution2d_4[0][0] 72 convolution2d_6[0][0] 73 convolution2d_8[0][0] 74 ____________________________________________________________________________________________________ 75 batchnormalization_9 (BatchNorma (None, 32, 32, 72) 288 merge_4[0][0] 76 ____________________________________________________________________________________________________ 77 activation_9 (Activation) (None, 32, 32, 72) 0 batchnormalization_9[0][0] 78 ____________________________________________________________________________________________________ 79 convolution2d_9 (Convolution2D) (None, 32, 32, 48) 3456 activation_9[0][0] 80 ____________________________________________________________________________________________________ 81 batchnormalization_10 (BatchNorm (None, 32, 32, 48) 192 convolution2d_9[0][0] 82 ____________________________________________________________________________________________________ 83 activation_10 (Activation) (None, 32, 32, 48) 0 batchnormalization_10[0][0] 84 ____________________________________________________________________________________________________ 85 convolution2d_10 (Convolution2D) (None, 32, 32, 12) 5184 activation_10[0][0] 86 ____________________________________________________________________________________________________ 87 merge_5 (Merge) (None, 32, 32, 84) 0 initial_conv2D[0][0] 88 convolution2d_2[0][0] 89 convolution2d_4[0][0] 90 convolution2d_6[0][0] 91 convolution2d_8[0][0] 92 convolution2d_10[0][0] 93 ____________________________________________________________________________________________________ 94 batchnormalization_11 (BatchNorm (None, 32, 32, 84) 336 merge_5[0][0] 95 ____________________________________________________________________________________________________ 96 activation_11 (Activation) (None, 32, 32, 84) 0 batchnormalization_11[0][0] 97 ____________________________________________________________________________________________________ 98 convolution2d_11 (Convolution2D) (None, 32, 32, 48) 4032 activation_11[0][0] 99 ____________________________________________________________________________________________________ 100 batchnormalization_12 (BatchNorm (None, 32, 32, 48) 192 convolution2d_11[0][0] 101 ____________________________________________________________________________________________________ 102 activation_12 (Activation) (None, 32, 32, 48) 0 batchnormalization_12[0][0] 103 ____________________________________________________________________________________________________ 104 convolution2d_12 (Convolution2D) (None, 32, 32, 12) 5184 activation_12[0][0] 105 ____________________________________________________________________________________________________ 106 merge_6 (Merge) (None, 32, 32, 96) 0 initial_conv2D[0][0] 107 convolution2d_2[0][0] 108 convolution2d_4[0][0] 109 convolution2d_6[0][0] 110 convolution2d_8[0][0] 111 convolution2d_10[0][0] 112 convolution2d_12[0][0] 113 ____________________________________________________________________________________________________ 114 batchnormalization_13 (BatchNorm (None, 32, 32, 96) 384 merge_6[0][0] 115 ____________________________________________________________________________________________________ 116 activation_13 (Activation) (None, 32, 32, 96) 0 batchnormalization_13[0][0] 117 ____________________________________________________________________________________________________ 118 convolution2d_13 (Convolution2D) (None, 32, 32, 96) 9216 activation_13[0][0] 119 ____________________________________________________________________________________________________ 120 averagepooling2d_1 (AveragePooli (None, 16, 16, 96) 0 convolution2d_13[0][0] 121 ____________________________________________________________________________________________________ 122 batchnormalization_14 (BatchNorm (None, 16, 16, 96) 384 averagepooling2d_1[0][0] 123 ____________________________________________________________________________________________________ 124 activation_14 (Activation) (None, 16, 16, 96) 0 batchnormalization_14[0][0] 125 ____________________________________________________________________________________________________ 126 convolution2d_14 (Convolution2D) (None, 16, 16, 48) 4608 activation_14[0][0] 127 ____________________________________________________________________________________________________ 128 batchnormalization_15 (BatchNorm (None, 16, 16, 48) 192 convolution2d_14[0][0] 129 ____________________________________________________________________________________________________ 130 activation_15 (Activation) (None, 16, 16, 48) 0 batchnormalization_15[0][0] 131 ____________________________________________________________________________________________________ 132 convolution2d_15 (Convolution2D) (None, 16, 16, 12) 5184 activation_15[0][0] 133 ____________________________________________________________________________________________________ 134 merge_7 (Merge) (None, 16, 16, 108) 0 averagepooling2d_1[0][0] 135 convolution2d_15[0][0] 136 ____________________________________________________________________________________________________ 137 batchnormalization_16 (BatchNorm (None, 16, 16, 108) 432 merge_7[0][0] 138 ____________________________________________________________________________________________________ 139 activation_16 (Activation) (None, 16, 16, 108) 0 batchnormalization_16[0][0] 140 ____________________________________________________________________________________________________ 141 convolution2d_16 (Convolution2D) (None, 16, 16, 48) 5184 activation_16[0][0] 142 ____________________________________________________________________________________________________ 143 batchnormalization_17 (BatchNorm (None, 16, 16, 48) 192 convolution2d_16[0][0] 144 ____________________________________________________________________________________________________ 145 activation_17 (Activation) (None, 16, 16, 48) 0 batchnormalization_17[0][0] 146 ____________________________________________________________________________________________________ 147 convolution2d_17 (Convolution2D) (None, 16, 16, 12) 5184 activation_17[0][0] 148 ____________________________________________________________________________________________________ 149 merge_8 (Merge) (None, 16, 16, 120) 0 averagepooling2d_1[0][0] 150 convolution2d_15[0][0] 151 convolution2d_17[0][0] 152 ____________________________________________________________________________________________________ 153 batchnormalization_18 (BatchNorm (None, 16, 16, 120) 480 merge_8[0][0] 154 ____________________________________________________________________________________________________ 155 activation_18 (Activation) (None, 16, 16, 120) 0 batchnormalization_18[0][0] 156 ____________________________________________________________________________________________________ 157 convolution2d_18 (Convolution2D) (None, 16, 16, 48) 5760 activation_18[0][0] 158 ____________________________________________________________________________________________________ 159 batchnormalization_19 (BatchNorm (None, 16, 16, 48) 192 convolution2d_18[0][0] 160 ____________________________________________________________________________________________________ 161 activation_19 (Activation) (None, 16, 16, 48) 0 batchnormalization_19[0][0] 162 ____________________________________________________________________________________________________ 163 convolution2d_19 (Convolution2D) (None, 16, 16, 12) 5184 activation_19[0][0] 164 ____________________________________________________________________________________________________ 165 merge_9 (Merge) (None, 16, 16, 132) 0 averagepooling2d_1[0][0] 166 convolution2d_15[0][0] 167 convolution2d_17[0][0] 168 convolution2d_19[0][0] 169 ____________________________________________________________________________________________________ 170 batchnormalization_20 (BatchNorm (None, 16, 16, 132) 528 merge_9[0][0] 171 ____________________________________________________________________________________________________ 172 activation_20 (Activation) (None, 16, 16, 132) 0 batchnormalization_20[0][0] 173 ____________________________________________________________________________________________________ 174 convolution2d_20 (Convolution2D) (None, 16, 16, 48) 6336 activation_20[0][0] 175 ____________________________________________________________________________________________________ 176 batchnormalization_21 (BatchNorm (None, 16, 16, 48) 192 convolution2d_20[0][0] 177 ____________________________________________________________________________________________________ 178 activation_21 (Activation) (None, 16, 16, 48) 0 batchnormalization_21[0][0] 179 ____________________________________________________________________________________________________ 180 convolution2d_21 (Convolution2D) (None, 16, 16, 12) 5184 activation_21[0][0] 181 ____________________________________________________________________________________________________ 182 merge_10 (Merge) (None, 16, 16, 144) 0 averagepooling2d_1[0][0] 183 convolution2d_15[0][0] 184 convolution2d_17[0][0] 185 convolution2d_19[0][0] 186 convolution2d_21[0][0] 187 ____________________________________________________________________________________________________ 188 batchnormalization_22 (BatchNorm (None, 16, 16, 144) 576 merge_10[0][0] 189 ____________________________________________________________________________________________________ 190 activation_22 (Activation) (None, 16, 16, 144) 0 batchnormalization_22[0][0] 191 ____________________________________________________________________________________________________ 192 convolution2d_22 (Convolution2D) (None, 16, 16, 48) 6912 activation_22[0][0] 193 ____________________________________________________________________________________________________ 194 batchnormalization_23 (BatchNorm (None, 16, 16, 48) 192 convolution2d_22[0][0] 195 ____________________________________________________________________________________________________ 196 activation_23 (Activation) (None, 16, 16, 48) 0 batchnormalization_23[0][0] 197 ____________________________________________________________________________________________________ 198 convolution2d_23 (Convolution2D) (None, 16, 16, 12) 5184 activation_23[0][0] 199 ____________________________________________________________________________________________________ 200 merge_11 (Merge) (None, 16, 16, 156) 0 averagepooling2d_1[0][0] 201 convolution2d_15[0][0] 202 convolution2d_17[0][0] 203 convolution2d_19[0][0] 204 convolution2d_21[0][0] 205 convolution2d_23[0][0] 206 ____________________________________________________________________________________________________ 207 batchnormalization_24 (BatchNorm (None, 16, 16, 156) 624 merge_11[0][0] 208 ____________________________________________________________________________________________________ 209 activation_24 (Activation) (None, 16, 16, 156) 0 batchnormalization_24[0][0] 210 ____________________________________________________________________________________________________ 211 convolution2d_24 (Convolution2D) (None, 16, 16, 48) 7488 activation_24[0][0] 212 ____________________________________________________________________________________________________ 213 batchnormalization_25 (BatchNorm (None, 16, 16, 48) 192 convolution2d_24[0][0] 214 ____________________________________________________________________________________________________ 215 activation_25 (Activation) (None, 16, 16, 48) 0 batchnormalization_25[0][0] 216 ____________________________________________________________________________________________________ 217 convolution2d_25 (Convolution2D) (None, 16, 16, 12) 5184 activation_25[0][0] 218 ____________________________________________________________________________________________________ 219 merge_12 (Merge) (None, 16, 16, 168) 0 averagepooling2d_1[0][0] 220 convolution2d_15[0][0] 221 convolution2d_17[0][0] 222 convolution2d_19[0][0] 223 convolution2d_21[0][0] 224 convolution2d_23[0][0] 225 convolution2d_25[0][0] 226 ____________________________________________________________________________________________________ 227 batchnormalization_26 (BatchNorm (None, 16, 16, 168) 672 merge_12[0][0] 228 ____________________________________________________________________________________________________ 229 activation_26 (Activation) (None, 16, 16, 168) 0 batchnormalization_26[0][0] 230 ____________________________________________________________________________________________________ 231 convolution2d_26 (Convolution2D) (None, 16, 16, 168) 28224 activation_26[0][0] 232 ____________________________________________________________________________________________________ 233 averagepooling2d_2 (AveragePooli (None, 8, 8, 168) 0 convolution2d_26[0][0] 234 ____________________________________________________________________________________________________ 235 batchnormalization_27 (BatchNorm (None, 8, 8, 168) 672 averagepooling2d_2[0][0] 236 ____________________________________________________________________________________________________ 237 activation_27 (Activation) (None, 8, 8, 168) 0 batchnormalization_27[0][0] 238 ____________________________________________________________________________________________________ 239 convolution2d_27 (Convolution2D) (None, 8, 8, 48) 8064 activation_27[0][0] 240 ____________________________________________________________________________________________________ 241 batchnormalization_28 (BatchNorm (None, 8, 8, 48) 192 convolution2d_27[0][0] 242 ____________________________________________________________________________________________________ 243 activation_28 (Activation) (None, 8, 8, 48) 0 batchnormalization_28[0][0] 244 ____________________________________________________________________________________________________ 245 convolution2d_28 (Convolution2D) (None, 8, 8, 12) 5184 activation_28[0][0] 246 ____________________________________________________________________________________________________ 247 merge_13 (Merge) (None, 8, 8, 180) 0 averagepooling2d_2[0][0] 248 convolution2d_28[0][0] 249 ____________________________________________________________________________________________________ 250 batchnormalization_29 (BatchNorm (None, 8, 8, 180) 720 merge_13[0][0] 251 ____________________________________________________________________________________________________ 252 activation_29 (Activation) (None, 8, 8, 180) 0 batchnormalization_29[0][0] 253 ____________________________________________________________________________________________________ 254 convolution2d_29 (Convolution2D) (None, 8, 8, 48) 8640 activation_29[0][0] 255 ____________________________________________________________________________________________________ 256 batchnormalization_30 (BatchNorm (None, 8, 8, 48) 192 convolution2d_29[0][0] 257 ____________________________________________________________________________________________________ 258 activation_30 (Activation) (None, 8, 8, 48) 0 batchnormalization_30[0][0] 259 ____________________________________________________________________________________________________ 260