posted by user: zhangyudong || 1172 views || tracked by 2 users: [display]

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


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

ML_BDA 2021   Special Issue on Machine Learning Technologies for Big Data Analytics
DMSE 2021   2nd International Conference on Data Mining and Software Engineering
Bio-inspired Deep Learning 2021   CFP: Bio-inspired Deep Learning Image and Signal Processing Pipelines in Medical Oncology - PeerJ
MEIJ 2021   Mechanical Engineering: An International Journal
NCAA 2022   Topical Collection on Deep Learning for Time Series Data for Neural Computing and Applications
EDTECH 2021   2nd International Conference on Education and Integrating Technology
MDPI mathematics 2021   MDPI mathematics - Special Issue on Computational Optimizations for Machine Learning
XSA 2021   Explainable Deep Learning for Sentiment Analysis
MMSys 2021   ACM Multimedia Systems Conference
IEEE DSAA 2021   8th IEEE International Conference on Data Science and Advanced Analytics