Using long short term memory and convolutional neural networks for driver drowsiness detection.

Fatigue negatively affects the safety and performance of drivers on the road. In fact, drowsiness and fatigue are the cause of a substantial number of motor vehicle accidents. Drowsiness among the drivers can be detected using variety of modalities, including electroencephalogram (EEG), eye movement, and vehicle driving dynamics.

Sustained vigilance is negatively affected by mild and acute sleep loss reflected by reduced capacity for decision making, motor preparation, and execution.

Study Objectives: The behavioral and cognitive consequences of severe sleep deprivation are well understood. Surprisingly, relatively little is known about the neural correlates of mild and acute sleep restriction on tasks that require sustained vigilance for prolonged periods of time during the day.

Methods And Results: Event-related potential (ERP) paradigms can reveal insight into the neural correlates underlying visual processing and behavioral responding that is impaired with reduced alertness, as a consequence of sleep loss.

Semantic image retrieval in magnetic resonance brain volumes.

Practitioners in the area of neurology often need to retrieve multimodal magnetic resonance (MR) images of the brain to study disease progression and to correlate observations across multiple subjects. In this paper, a novel technique for retrieving 2-D MR images (slices) in 3-D brain volumes is proposed. Given a 2-D MR query slice, the technique identifies the 3-D volume among multiple subjects in the database, associates the query slice with a specific region of the brain, and retrieves the matching slice within this region in the identified volumes.

Adaboost and Support Vector Machines for White Matter Lesion Segmentation in MR Images.

The use of two powerful classification techniques (boosting and SVM) is explored for the segmentation of white-matter lesions in the MRI scans of human brain. Simple features are generated from Proton Density (PD) scans. Radial Basis Function (RBF) based Adaboost technique and Support Vector Machines (SVM) are employed for this task.