posted by user: zhangyudong || 957 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

DLMIA 2020   Deep Learning on Medical Image Analysis - Journal of Imaging (ESCI)
IEEE-CVIV 2020   2020 2nd International Conference on Advances in Computer Vision, Image and Virtualization (CVIV 2020)
EI/SCOPUS-CMVIT 2021   5th International Conference on Machine Vision and Information Technology (CMVIT 2021)
AICA 2020   O'Reilly AI Conference San Jose
MNLP 2020   4th IEEE Conference on Machine Learning and Natural Language Processing
EDLTMBE 2020   Emerging Deep Learning Theories and Methods for Biomedical Engineering - IEEE Access (IF: 4.098)
AICI 2021   The Second International Conference on Artificial Intelligence and Computational Intelligence (AICI 2021)
MAAIDL 2020   Springer Book 'Malware Analysis using Artificial Intelligence and Deep Learning'
MLT 2020   International Conference on Machine Learning & Trends
Fintech 2020   Sustainaility (Q2): Fintech: Recent Advancements in Modern Techniques, Methods and Real-World Solutions