AIMC Topic: Deep Learning

Clear Filters Showing 19131 to 19140 of 28423 articles

From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?

Environmental science & technology
Dissolved oxygen (DO) reflects river metabolic pulses and is an essential water quality measure. Our capabilities of forecasting DO however remain elusive. Water quality data, specifically DO data here, often have large gaps and sparse areal and temp...

Aggregation of cohorts for histopathological diagnosis with deep morphological analysis.

Scientific reports
There have been substantial efforts in using deep learning (DL) to diagnose cancer from digital images of pathology slides. Existing algorithms typically operate by training deep neural networks either specialized in specific cohorts or an aggregate ...

Deep learning for the fully automated segmentation of the inner ear on MRI.

Scientific reports
Segmentation of anatomical structures is valuable in a variety of tasks, including 3D visualization, surgical planning, and quantitative image analysis. Manual segmentation is time-consuming and deals with intra and inter-observer variability. To dev...

Reconstructing Undersampled Photoacoustic Microscopy Images Using Deep Learning.

IEEE transactions on medical imaging
One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed. In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM imag...

Deep learning framework for subject-independent emotion detection using wireless signals.

PloS one
Emotion states recognition using wireless signals is an emerging area of research that has an impact on neuroscientific studies of human behaviour and well-being monitoring. Currently, standoff emotion detection is mostly reliant on the analysis of f...

A Transfer Learning Based Super-Resolution Microscopy for Biopsy Slice Images: The Joint Methods Perspective.

IEEE/ACM transactions on computational biology and bioinformatics
Higher-resolution biopsy slice images reveal many details, which are widely used in medical practice. However, taking high-resolution slice images is more costly than taking low-resolution ones. In this paper, we propose a joint framework containing ...

ResNet-SCDA-50 for Breast Abnormality Classification.

IEEE/ACM transactions on computational biology and bioinformatics
(Aim) Breast cancer is the most common cancer in women and the second most common cancer worldwide. With the rapid advancement of deep learning, the early stages of breast cancer development can be accurately detected by radiologists with the help of...

A Deep Segmentation Network of Multi-Scale Feature Fusion Based on Attention Mechanism for IVOCT Lumen Contour.

IEEE/ACM transactions on computational biology and bioinformatics
Recently, coronary heart disease has attracted more and more attention, where segmentation and analysis for vascular lumen contour are helpful for treatment. And intravascular optical coherence tomography (IVOCT) images are used to display lumen shap...

GrantExtractor: Accurate Grant Support Information Extraction from Biomedical Fulltext Based on Bi-LSTM-CRF.

IEEE/ACM transactions on computational biology and bioinformatics
Grant support (GS) in the MEDLINE database refers to funding agencies and contract numbers. It is important for funding organizations to track their funding outcomes from the GS information. As such, how to accurately and automatically extract fundin...

An Integrative Framework for Combining Sequence and Epigenomic Data to Predict Transcription Factor Binding Sites Using Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Knowing the transcription factor binding sites (TFBSs) is essential for modeling the underlying binding mechanisms and follow-up cellular functions. Convolutional neural networks (CNNs) have outperformed methods in predicting TFBSs from the primary D...