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Deep Autoencoder-Based Image Compression using Multi-Layer Perceptrons
2020
International journal of soft computing and engineering
The Artificial Neural Network is one of the heavily used alternatives for solving complex problems in machine learning and deep learning. In this research, a deep autoencoder-based multi-layer feed-forward neural network has been proposed to achieve image compression. The proposed neural network splits down a large image into small blocks and each block applies the normalization process as the preprocessing technique. Since this is an autoencoder-based neural network, each normalized block of
doi:10.35940/ijsce.e3357.039620
fatcat:o3qzl5ufmzhobg5h7gqofedxpe