"The AWCFT will initially provide computer vision algorithms for object detection, classification and alerts for FMV PED.
These stages are: ROI generation, detection, classification, and tracking.
The output of the scheme can be used for fault detection, classification and location.
The data is analyzed for the fault detection classification (FDC) mechanism using deep learning based analytics.
This includes tasks such as autonomous take-off and landing, waypoint navigation, automatic in-flight obstacle avoidance, target detection, classification and localization, and payload delivery.
A dynamic neural network aggregation (DNNA) model was proposed for transient detection, classification and prediction in nuclear power plants.
The crack detection, classification and estimation of the geometrical characteristics, for different classes of defects, are described in the paper.
The paper presents a new digital relaying for detection, classification and localization of faults on the hybrid transmission line consisting of an overhead line and an underground cable.
The paper provides fault detection, classification and location of the open circuit (O-C) faults which do not trigger the standard protection systems in the single-phase inverters.
Several research projects have used this data to test artifact detection, classification, transfer learning, EEG preprocessing, blink detection, and automated annotation algorithms.
Strategies and essential image processing routines necessary for making the appropriate decision during detection, classification, identification, quantification and/or prediction processes are presented.
