x_train = x_train.astype('float32') / 255. x_test = x_test.astype('float32') / 255. x_train = x_train.reshape((len(x_train), np.prod(x_train.shape[1:]))) x_test = x ...
Abstract: 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 ...
Abstract: Deep learning has shown broad research prospects in addressing insider threats, a serious problem currently facing industrial information systems. Although deep learning is able to capture ...
This code has been implemented in python language using Pytorch framework. Following environements and libraries are needed to run the code: Python 3 torch version 1.12.0 torchvision 0.13.0 The ...
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