Special Issue "Application of Entropy to Computer Vision and Medical Imaging"
Deadline for manuscript submissions: 31 August 2022 | Viewed by 3944
Interests: image processing; pattern recognition; medical image analysis; information fusion
Shannon entropy is initially devoted to quantifying the minimum bits necessary to encode a signal without loss of information; it represents the asymptotic limit of the compression ratio in the Huffman algorithm. Moreover, Shannon entropy is linked to the amount of disorder in random signals. Since Shannon’s work, generalizations of entropy (Rényie, Havrda–Charvat) as well as various applications have emerged. In statistics, as well as in machine learning, different entropies have been used to model uncertainty in data and in parameter estimation and can be also used to evaluate the amount of information in data. From entropies, one can define divergences which are used as “distances” between probability distributions. In deep learning, these entropies are usually used as loss functions for probabilistic neural networks.
This Special Issue is devoted to applications of probabilistic neural networks for computer vision and medical image analysis.
This Special Issue will accept unpublished original papers and comprehensive reviews focused on (but not restricted to) the following research areas:
- Modeling new loss functions in neural networks;
- Use of entropies and information measures for uncertainty quantification in a neural network;
- Choice of relevant entropy depending on the data and the task;
- Influence of activation functions on the choice of entropy;
- Axioms behind the choice of entropy;
- Entropy measures for the evaluation of image quality;
- Applications to medical image analysis and computer vision.
Dr. Su Ruan
Dr. Jérôme Lapuyade-Lahorgue
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- shannon entropy
- generalized entropies
- uncertainty quantification
- deep learning
- medical image analysis
- computer vision
- amount of information