AIMC Topic: Deep Learning

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Deep Learning and Transformer Approaches for UAV-Based Wildfire Detection and Segmentation.

Sensors (Basel, Switzerland)
Wildfires are a worldwide natural disaster causing important economic damages and loss of lives. Experts predict that wildfires will increase in the coming years mainly due to climate change. Early detection and prediction of fire spread can help red...

Accurate Physical Property Predictions via Deep Learning.

Molecules (Basel, Switzerland)
Neural networks and deep learning have been successfully applied to tackle problems in drug discovery with increasing accuracy over time. There are still many challenges and opportunities to improve molecular property predictions with satisfactory ac...

COVID-19 Identification System Using Transfer Learning Technique With Mobile-NetV2 and Chest X-Ray Images.

Frontiers in public health
Diagnosis is a crucial precautionary step in research studies of the coronavirus disease, which shows indications similar to those of various pneumonia types. The COVID-19 pandemic has caused a significant outbreak in more than 150 nations and has si...

Detection of Breast Cancer Using Histopathological Image Classification Dataset with Deep Learning Techniques.

BioMed research international
Cancer is one of the top causes of mortality, and it arises when cells in the body grow abnormally, like in the case of breast cancer. For people all around the world, it has now become a huge issue and a threat to their safety and wellbeing. Breast ...

Convolutional LSTM: a deep learning approach to predict shoulder joint reaction forces.

Computer methods in biomechanics and biomedical engineering
We developed a Convolutional LSTM (ConvLSTM) network to predict shoulder joint reaction forces using 3D shoulder kinematics data containing 30 different shoulder activities from eight human subjects. We considered simulation outcomes from the AnyBody...

Defining Normal Ranges of Skeletal Muscle Area and Skeletal Muscle Index in Children on CT Using an Automated Deep Learning Pipeline: Implications for Sarcopenia Diagnosis.

AJR. American journal of roentgenology
Skeletal muscle area (SMA), representing skeletal muscle cross-sectional area at the L3 vertebral level, and skeletal muscle index (SMI), representing height-normalized SMA, can serve as markers of sarcopenia. Normal SMA and SMI values have been rep...

Application of deep learning in teeth identification tasks on panoramic radiographs.

Dento maxillo facial radiology
OBJECTIVES: To investigate the current developments of Artificial Intelligence (AI) in teeth identification on Panoramic Radiographs (PR). Our aim was to evaluate and compare the performances of Deep Learning (DL) models that have been employed in th...

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.

Medical image analysis
Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic disorders can be decomposed into useful imaging features such as time courses (TCs) of independent components (ICs) and functional network connectivity (FNC) ca...

Deep learning for predicting respiratory rate from biosignals.

Computers in biology and medicine
In the past decade, deep learning models have been applied to bio-sensors used in a body sensor network for prediction. Given recent innovations in this field, the prediction accuracy of novel models needs to be evaluated for bio-signals. In this pap...

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis.

Microbiology spectrum
Images of laser scattering patterns generated by bacteria in urine are promising resources for deep learning. However, floating bacteria in urine produce dynamic scattering patterns and require deep learning of spatial and temporal features. We hypot...