Despite their huge potential, deep learning-based models are still not trustful enough to warrant their adoption in clinical practice. The research on the interpretability and explainability of deep learning is currently attracting huge attention. …
Over time, crack pattern (craquelure) inevitably develops in paintings as a sign of their ageing, sometimes accompanied by larger losses of paint (lacunas). In restoration treatments, cracks are typically not filled in, and virtual restoration is …
With the ever-increasing availability of data, the need for efficient and accurate image retrieval methods has become larger and larger. Deep hashing has proven to be a promising solution, by defining a hash function to convert the data into a …
Block matching is a fundamental tool to search blocks (patches) similar or identical to a given query in image processing. Generally, a full search (FS) algorithm is the most accurate but requires vast computation especially in multichannel images, …
Conditional Variational Auto Encoders (VAE) are gathering significant attention as an Explainable Artificial Intelligence (XAI) tool. The codes in the latent space provide a theoretically sound way to produce counterfactuals, i.e. alterations …
In this paper, we propose an efficient method for learning local image descriptor and its inversion function using a variational autoencoder (VAE). We design a loss function of the VAE specifically for this purpose, which, on one hand, incentivises …