Fault detection and diagnosis to enhance safety in digitalized process system

The increased complexity of digitalized process systems requires advanced tools to detect and diagnose faults early to maintain safe operations. This study proposed a hybrid model that consists of Kernel Principal Component Analysis (kPCA) and DNNs that can be applied to detect and diagnose faults in various processes. The complex data is...

Gas leakage detection using spatial and temporal neural network model

Natural gas leakage can impose significant danger on a facility and its surrounding communities. Methods for early detection and diagnosis of such leakages have been developed and widely used for gas pipelines and storage tanks. Most techniques include inspection of sensor-aided mathematical models. Application of machine learning techniques to...

Multi-frame deep learning models for action detection in surveillance videos

Visual surveillance technologies are increasingly being used to monitor public spaces. These technologies process the recordings of surveillance cameras. Such recordings contain depictions of human actions such as "running", "waving", and "aggression". In the field of computer vision, automated detection of human actions in videos is known as...

Collision Avoidance for Predefined C-arm Trajectory using 3D Depth Measurements

Human-robot collaborative act is obvious nowadays in a modern intervention room. It is very important to ensure the safety of the patient along with other personnel in the operation theater and prevent damages to the equipment during an intervention. Due to the complex environment and multiple unknown dynamic objects in the room, vision-based...