Special Issue "Artificial Neural Networks in Pattern Recognition"
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: closed (1 November 2020).
Interests: artificial intelligence; deep learning; neural networks
The 9th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, will be held from September 2 to September 4, 2020, at Zurich University of Applied Sciences ZHAW in Winterthur, Switzerland. The workshop is a major forum for international researchers and practitioners working in all areas of neural network- and machine learning-based pattern recognition to present and discuss the latest research, results, and ideas in these areas. ANNPR is the biannual workshop organized by the Technical Committe 3 (TC3) on Neural Networks & Computational Intelligence of the International Association for Pattern Recognition (IAPR). For more information about the workshop, please use the following link: https://annpr2020.ch/.
Selected papers that are presented at the workshop will be invited to submit extended versions to this Special Issue of Computers after the conference. All selected papers will free of charge if they are accepted after peer review. Submitted papers should be extended to the length of regular research or review articles, with at least 50% coverage of new results. All submitted papers will undergo our standard peer-review procedure. Accepted papers will be published in open access format in Computers and collected together in this Special Issue. There are no page limitations for this journal.
We are also inviting original research work covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in artificial neural networks in pattern recognition. The main topics include, but are not limited to, the following:
- Supervised, semi-supervised, unsupervised, and reinforcement learning;
- Deep learning and deep reinforcement learning;
- Feed-forward, recurrent, and convolutional neural networks;
- Generative models;
- Interpretability and explainability of neural networks;
- Robustness and generalization of neural networks;
- Meta-learning (ML) and auto-ML.
Applications to pattern recognition:
- Image classification and segmentation;
- Object detection;
- Document analysis, e.g., handwriting recognition;
- Sensor-fusion and multi-modal processing;
- Biometrics, including speech and speaker recognition and segmentation;
- Data, text, and web mining;
- Bioinformatics and medical applications;
- Industrial applications, e.g., quality control and predictive maintenance.
Dr. Frank-Peter Schilling
Prof. Dr. Thilo Stadelmann
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 papers will be 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. Computers 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 1400 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.