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Single-frame infrared small-target detection: A survey
Compared with radar and visible light imaging, infrared imaging has its own unique
advantages, and in recent years, it has become a topic of intense research interest. Robust …
advantages, and in recent years, it has become a topic of intense research interest. Robust …
Credal Bayesian deep learning
Uncertainty quantification and robustness to distribution shifts are important goals in
machine learning and artificial intelligence. Although Bayesian Neural Networks (BNNs) …
machine learning and artificial intelligence. Although Bayesian Neural Networks (BNNs) …
Relative information loss in the PCA
In this work we analyze principle component analysis (PCA) as a deterministic input-output
system. We show that the relative information loss induced by reducing the dimensionality of …
system. We show that the relative information loss induced by reducing the dimensionality of …
Magnetic resonance image quality assessment by using non-maximum suppression and entropy analysis
An investigation of diseases using magnetic resonance (MR) imaging requires automatic
image quality assessment methods able to exclude low-quality scans. Such methods can be …
image quality assessment methods able to exclude low-quality scans. Such methods can be …
Blind image quality assessment of magnetic resonance images with statistics of local intensity extrema
Magnetic resonance (MR) imaging provides a large amount of data that requires a visual
inspection before a diagnosis can be made. Since the exclusion of low-quality image …
inspection before a diagnosis can be made. Since the exclusion of low-quality image …
Efficient mixture model for clustering of sparse high dimensional binary data
Clustering is one of the fundamental tools for preliminary analysis of data. While most of the
clustering methods are designed for continuous data, sparse high-dimensional binary …
clustering methods are designed for continuous data, sparse high-dimensional binary …
[ספר][B] Information Loss in Deterministic Signal Processing Systems
Springer Complexity is an interdisciplinary program publishing the best research and
academic-level teaching on both fundamental and applied aspects of complex systems …
academic-level teaching on both fundamental and applied aspects of complex systems …
Background suppression of small target image based on fast local reverse entropy operator
Background suppression is vitally important for the small target detection, which aims to
enhance targets and improve the signal‐to‐noise ratio of small target images …
enhance targets and improve the signal‐to‐noise ratio of small target images …
Weighted approach to general entropy function
The definition of weighted entropy allows to calculate the entropy of the mixture of measures.
In this paper, we investigate the problem of equivalent definition of the general entropy …
In this paper, we investigate the problem of equivalent definition of the general entropy …
[PDF][PDF] Information loss in deterministic systems
A typical PhD thesis is a highly specialized piece of work: Metaphorically speaking, the
scientist has to climb a mountain (the scientific field), find a tree on this mountain (the …
scientist has to climb a mountain (the scientific field), find a tree on this mountain (the …