As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

X-ray diffraction/scattering computed tomography (XDS-CT) methods are a non-destructive
class of chemical imaging techniques that have the capacity to provide reconstructions of …

Video surveillance systems are used to enhance the public safety and private assets.
Automatic anomaly detection is vital in such surveillance systems to reduce the human labor …

Anomaly detection from video surveillance inputs helps to improve security in crowded
places and outdoors. The captured image is analyzed to identify human faces, objects, and …

Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …

Multimedia anomaly datasets play a crucial role in automated surveillance. They have a
wide range of applications expanding from outlier objects/situation detection to the detection …

The left ventricular of ejection fraction is one of the most important metric of cardiac function.
It is used by cardiologist to identify patients who are eligible for life-prolonging therapies …

To optimize and predict the catalyst for precise synthesis of methyl glycolate (MG) from
dimethyl oxalate, this study proposed a six-step machine learning framework coupled with a …

Within food production in agriculture, different sensor networks are used to manage and
monitor different processes, ranging from the presence of certain plant nutrients in soil to the …

The framework provides a novel pipeline for action recognition. The action recognition task
classifies the action label of the scene. High-speed cameras are commonly used to generate …