In this article, we propose a stack autoencoder transfer learning algorithm based on the class separation and domain fusion (SAE-CSDF) to solve these problems. According to the characteristics of ...

sparse_reg]) For stacked autoencoder, there are more than one autoencoder in this network, in the script of "SAE_Softmax_MNIST.py", I defined two autoencoders: corruption_level = 0.3 sparse_reg = 0 # ...

Number of nodes per layer: the autoencoder architecture we’re working on is called a stacked autoencoder since the layers are stacked one after another. Usually stacked The stacked auto-encoders is a ...

In this paper, we first propose a stacked autoencoder (SAE) and bi-directional long short-term memory (Bi-LSTM) based spectrum prediction method (SAEL-SP). Specifically, a SAE is designed to extract ...

We employed time–frequency analysis (TFA) and a stacked autoencoder (SAE), which is a deep neural network (DNN)-based learning algorithm, to assess the mobility and fall risk of the elderly according ...

We present a novel granular computing approach that assesses landslide risk by combining fuzzy information granulation and a stacked autoencoder algorithm. The stacked autoencoder is trained using an ...

SHENZHEN, China, Feb. 14, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, they Announced the ...