posted by user: zhangyudong || 337 views || tracked by 2 users: [display]

ADLMBIA 2020 : Advanced Deep Learning Methods for Biomedical Information Analysis (IF: 2.031)

FacebookTwitterLinkedInGoogle

Link: https://www.frontiersin.org/research-topics/9687/advanced-deep-learning-methods-for-biomedical-information-analysis-adlmbia
 
When N/A
Where N/A
Abstract Registration Due Nov 4, 2019
Submission Deadline Dec 1, 2019
Notification Due Feb 1, 2020
Final Version Due Mar 1, 2020
Categories    deep learning   trans fer learning   biomedical signal   information analysis
 

Call For Papers

Deep learning approaches have been rapidly developed in recent years, both in terms of methodologies and practical applications. Deep learning techniques provide computational models of multiple processing layers to learn and represent data with multiple levels of abstraction. Deep Learning allows to implicitly capture intricate structures of large-scale data and ideally suited to some of the hardware architectures that are currently available.

The purpose of this Article Collection is to provide a diverse, but complementary, set of contributions to demonstrate new developments and applications of Deep learning and Computational Machine Learning, to solve problems in biomedical engineering. The ultimate goal is to promote research and development of deep learning for multimodal biomedical images by publishing high-quality research articles, reviews, or perspectives, among other article types, in this rapidly growing interdisciplinary field.

Topics include, but are not limited to:
- Theoretical understanding of deep learning in biomedical engineering
- Transfer learning and multi-task learning
- Joint Semantic Segmentation, Object Detection and Scene Recognition on biomedical images
- Improvising on the computation of a deep network, exploiting parallel computation techniques
and GPU programming
- Multimodal imaging techniques (data acquisition, reconstruction, 2D, 3D, 4D imaging, etc.)
- Translational multimodality imaging and biomedical applications (e.g., detection, diagnostic
analysis, quantitative measurements, image guidance of ultrasonography)
- Optimization by deep neural networks, Multi-dimensional deep learning
- New Model of New Structure of convolutional neural network
- Visualization and Explainable deep neural network


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

All accepted papers will be published on one of those journals: Frontiers in Big Data, Frontiers in Artificial Intelligence, Frontiers in Public Health (IF: 2.031), or Frontiers in Computer Science. The authors need to specify the journal during their submission procedure.

Related Resources

EWRE-EI/Scopus 2019   2019 2nd International Conference on Environmental and Water Resources Engineering
IPMU 2020   18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
ICMLC--ACM, Ei and Scopus 2020   ACM--2020 12th International Conference on Machine Learning and Computing (ICMLC 2020)--SCOPUS, Ei Compendex
ICDEL--Ei Compendex and Scopus 2020   2020 the 5th International Conference on Distance Education and Learning (ICDEL 2020)--Ei Compendex, Scopus
DASFAA 2020   Database Systems for Advanced Applications
IJCSA 2019   International Journal on Computational Science & Applications
IJSCAI 2019   International Journal on Soft Computing, Artificial Intelligence and Applications
ETRIJ 5G&B5G 2020   ETRI Journal Special Issue on 5G & B5G Enabling Edge Computing, Big Data & Deep Learning Technologies
ICABB--Ei Compendex and Scopus 2019   2019 International Conference on Advanced Bioinformatics and Biomedical Engineering (ICABB 2019)--Ei Compendex and Scopus
BIOINFORMATICS 2020   11th International Conference on Bioinformatics Models, Methods and Algorithms