In this project we will use the Fashion MNIST computer vision digit dataset and experiment with auto-encoders such as Variational Auto-encoder(VAE) and simple autoencoder. Figure3: A: A sample ...
Deep Autoencoder for Handwritten Digits MNIST This project demonstrates the implementation of a Deep Autoencoder using Keras and TensorFlow to encode and reconstruct handwritten digits from the ...
Abstract: Self-supervised learning through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) image representation learning (IRL), and thus embodies a ...
Variational Autoencoders (VAEs) are an artificial neural network architecture to generate new data. They are similar to regular autoencoders, which consist of an encoder and decoder. The encoder takes ...
Abstract: We investigated the adaptation and performance of Masked Autoencoders (MAEs) with Vision Transformer (ViT) architectures for self-supervised representation learning on one-dimensional (1D) ...
ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...
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