问题描述
我正在研究一个无监督的图像分类问题，该数据集包含约4700张食肉动物照片。我想到了通过构造自动编码器并获取图像嵌入，然后应用余弦相似度来实现此任务的方法。我没有太大的进步。这是我的自动编码器体系结构：
Model: "functional_75"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_19 (InputLayer) [(None,128,3)] 0
_________________________________________________________________
conv2d_126 (Conv2D) (None,64) 1792
_________________________________________________________________
max_pooling2d_54 (MaxPooling (None,64,64) 0
_________________________________________________________________
conv2d_127 (Conv2D) (None,32) 18464
_________________________________________________________________
max_pooling2d_55 (MaxPooling (None,32,32) 0
_________________________________________________________________
conv2d_128 (Conv2D) (None,16) 4624
_________________________________________________________________
max_pooling2d_56 (MaxPooling (None,16,16) 0
_________________________________________________________________
conv2d_129 (Conv2D) (None,16) 2320
_________________________________________________________________
up_sampling2d_54 (UpSampling (None,16) 0
_________________________________________________________________
conv2d_130 (Conv2D) (None,32) 4640
_________________________________________________________________
up_sampling2d_55 (UpSampling (None,32) 0
_________________________________________________________________
conv2d_131 (Conv2D) (None,64) 18496
_________________________________________________________________
conv2d_132 (Conv2D) (None,3) 1731
_________________________________________________________________
up_sampling2d_56 (UpSampling (None,3) 0
=================================================================
Total params: 52,067
Trainable params: 52,067
Non-trainable params: 0
_________________________________________________________________
请提出一些改进建议。
解决方法
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