Tensorflow初学笔记——tf.nn.conv2d()的工作方法答:tf.nn.conv2d()函数有六个参数,其中input是输入图片([batch, 长, 宽, 通道数]),filter是卷积核([长, 宽, 输入通道数, 输出通道数]),strides定义了卷积核的移动步长,而padding则控制了边缘处理方式。以一个实例来说明:假设输入数据是[100, 80, 100, 4],卷积核是[8, 8, 4, 32]...
地震去噪新探索(二)——无监督卷积神经网络调优实战答:x = Conv2D(32, (3, 3), activation='relu', padding='same')(input_img)x = Conv2D(32, (3, 3), activation='relu', padding='same')(x)x = Conv2DTranspose(32, (3,3), padding='same', activation='relu', kernel_initializer='glorot_normal')(x)#反卷积 x = Conv2D...