Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review
Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …
tools in medicine and healthcare. Deep learning methods have achieved promising results …
Accelerating materials discovery using machine learning
Y Juan, Y Dai, Y Yang, J Zhang - Journal of Materials Science & …, 2021 - Elsevier
The discovery of new materials is one of the driving forces to promote the development of
modern society and technology innovation, the traditional materials research mainly …
modern society and technology innovation, the traditional materials research mainly …
Driver behavior detection and classification using deep convolutional neural networks
Driver behavior monitoring system as Intelligent Transportation Systems (ITS) have been
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …
Driver stress detection via multimodal fusion using attention-based CNN-LSTM
Stress has been identified as one of major contributing factors in car crashes due to its
negative impact on driving performance. It is in urgent need that the stress levels of drivers …
negative impact on driving performance. It is in urgent need that the stress levels of drivers …
Deep learning-based construction equipment operators' mental fatigue classification using wearable EEG sensor data
Operator attention failure due to mental fatigue during extended equipment operations is a
common cause of equipment-related accidents that result in catastrophic injuries and …
common cause of equipment-related accidents that result in catastrophic injuries and …
Audio based depression detection using Convolutional Autoencoder
Depression is a serious and common psychological disorder that requires early diagnosis
and treatment. In severe episodes the condition may result in suicidal thoughts. Recently …
and treatment. In severe episodes the condition may result in suicidal thoughts. Recently …
HRV features as viable physiological markers for stress detection using wearable devices
KM Dalmeida, GL Masala - Sensors, 2021 - mdpi.com
Stress has been identified as one of the major causes of automobile crashes which then
lead to high rates of fatalities and injuries each year. Stress can be measured via …
lead to high rates of fatalities and injuries each year. Stress can be measured via …
Human-machine shared driving: Challenges and future directions
Distraction, misjudgement and driving mistakes can significantly affect a driver, resulting in
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …
DSDCLA: Driving style detection via hybrid CNN-LSTM with multi-level attention fusion
Driving style detection is an essential real-world requirement in diverse contexts, such as
traffic safety, car insurance and fuel consumption optimization. However, the existing …
traffic safety, car insurance and fuel consumption optimization. However, the existing …
Real-time detection of abnormal driving behavior based on long short-term memory network and regression residuals
Abnormal driving behavior is one of the main causes of roadway collisions. In most studies
of abnormal driving behavior, the abnormal driving status is detected and analyzed using …
of abnormal driving behavior, the abnormal driving status is detected and analyzed using …