U
Usman Ali
Researcher at College of Electrical and Mechanical Engineering
Publications - 28
Citations - 264
Usman Ali is an academic researcher from College of Electrical and Mechanical Engineering. The author has contributed to research in topics: Computer science & Regularization (linguistics). The author has an hindex of 5, co-authored 17 publications receiving 118 citations. Previous affiliations of Usman Ali include University of the Sciences & National University of Sciences and Technology.
Papers
More filters
Journal ArticleDOI
A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays
TL;DR: A novel approach that utilizes deep two-dimensional (2-D) Convolutional Neural Networks to extract features from 2-D scalograms generated from PV system data in order to effectively detect and classify PV system faults is presented.
Proceedings ArticleDOI
FPGA/soft-processor based real-time object tracking system
TL;DR: A low cost FPGA based solution for a real-time moving object tracking system based on a soft RISC processor capable of running kernel based mean shift tracking algorithm within the required time constraint is presented.
Journal ArticleDOI
Hardware/software co-design of a real-time kernel based tracking system
Usman Ali,Mohammad Bilal Malik +1 more
TL;DR: A hardware/software co-design architecture for implementation of the well-known kernel based mean shift tracking algorithm based on gradient based iterative search instead of exhaustive search which makes the system capable of achieving frame rate up to hundreds of frames per second while tracking multiple targets.
Journal ArticleDOI
Development of Frequency Weighted Model Reduction Algorithm with Error Bound: Application to Doubly Fed Induction Generator Based Wind Turbines for Power System
TL;DR: This paper deals with the model order reduction of the Variable-Speed Wind Turbines model with the aid of improved stability preserving a balanced realization algorithm based on frequency weighting.
Proceedings ArticleDOI
Development of Frequency Limited Model Reduction Algorithm with Error Bound and Application to Continuous-Time Variable-Speed Wind Turbines for Power System
TL;DR: In this paper, the proposed approach not only ensures the stability of the reduced-order systems but also provides low approximation error when compared with existing approaches, but also yield easily computable a priori error bound formula.