Unlike other deep learning (DL) models, Transformer has the ability to extract long-range dependency features from hyperspectral image (HSI) data. Masked autoencoder (MAE), which is based on ...

Block-diagonal representation (BDR) is an effective subspace clustering method. The existing BDR methods usually obtain a self-expression coefficient matrix from the original features by a shallow ...

Each thin blue arrow represents a neural weight, which is just a number, typically between about -2 and +2. Weights are sometimes called trainable parameters. The small red arrows are special weights ...

The Convolutional Block Attention Module (Woo et al., 2018) consists of two sub-modules: the Channel Attention Module and the Spatial Attention Module. By adaptively refining intermediate feature maps ...

Each small blue arrow represents a neural weight, which is just a number, typically between about -2 and +2. Weights are sometimes called trainable parameters. The small red arrows are special weights ...

This was an experiment for a possible PhD topic. The main idea was to use different Autoencoder for entity resolution / product matching. The core idea was to pretrain an Autoencoder on the positive ...

Block diagram of the safflower picking robot. The complete machine diagram of the safflower picking robot is shown in Fig. 2. The safflower picking robot operation process is as follows. The robot is ...

Article citations More>> Ng, A. (2011) Sparse Autoencoder. CS294A Lecture Notes, 72, 1-19. has been cited by the following article: TITLE: A Double-Weighted Deterministic Extreme Learning Machine ...