Recently, learning algorithms such as Convolutional Neural Networks have been
successfully applied in different stages of data processing from the acquisition to the data …

Mental stress has been identified as a significant cause of several bodily disorders, such as
depression, hypertension, neural and cardiovascular abnormalities. Conventional stress …

We present the application of limited one-time sampling irregularity map (LOTS-IM): a fully
automatic unsupervised approach to extract brain tissue irregularities in magnetic …

White Matter Hyperintensities (WMHs) are neu-roradiological features often seen in T2-
FLAIR brain MRI as white regions (ie, hyperintensities) and characteristic of small vessel …

Deep-learning techniques have been used widely to alleviate the labour-intensive and time-
consuming manual annotation required for pixel-level tissue characterization. Our previous …

Chatbot as a conversational system that can interact with human naturally is a Natural
Language Processing task that require modeling semantics of complicated relationships of …

Im Kontext automatisierter Datenauswertung sind künstliche neuronale Faltungsnetzwerke
und der Einsatz von Deep-Learning-Ansätzen mittlerweile Stand der Technik. Im Bereich …

Abstract Machine learning algorithms underpin modern diagnostic-aiding software, which
has proved valuable in clinical practice, particularly in radiology. However, inaccuracies …

We propose a novel approach named one-time sampling irregularity age map (OTS-IAM) to
detect any irregular texture in FLAIR brain MRI without any human supervision or interaction …

Traffic congestion causes traveler delay, environmental deterioration, and economic loss.
Most studies on congestion mitigation focus on attracting travelers to public transportation …