M
Muhammad Abbas
Researcher at University of the Sciences
Publications - 55
Citations - 302
Muhammad Abbas is an academic researcher from University of the Sciences. The author has contributed to research in topics: Project management & Software. The author has an hindex of 7, co-authored 54 publications receiving 176 citations. Previous affiliations of Muhammad Abbas include College of Electrical and Mechanical Engineering & National University of Science and Technology.
Papers
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Proceedings ArticleDOI
The Influence of Agile Methodology (Scrum) on Software Project Management
TL;DR: Survey from different software companies shows that almost every software company uses agile development (Scrum) and has a positive impact on the software project management.
Proceedings ArticleDOI
Scrum Software Maintenance Model: Efficient Software Maintenance in Agile Methodology
TL;DR: The theoretical and empirical technique is used to formulate factors that should be followed during the agile maintenance including planning for the maintenance; the on-site customer should be present, iterative maintenance, documentation update after each phase and maintenance should be testable.
Journal ArticleDOI
Self-Organizing Hierarchical Particle Swarm Optimization of Correlation Filters for Object Recognition
Sara Tehsin,Saad Rehman,Muhammad Omer Bin Saeed,Farhan Riaz,Ali Hassan,Muhammad Abbas,Rupert Young,Mohammad S. Alam +7 more
TL;DR: The OT parameters are optimized using particle swarm optimization with respect to two different cost functions to achieve the best possible result for each scenario.
Proceedings ArticleDOI
Traffic event detection from road surveillance vide os based on fuzzy logic
TL;DR: A novel Fuzzy Logic based analysis framework and a video based traffic data extraction scheme to decide upon the right traffic conditions are presented and are seen to be robust enough to reject the noisy data coming from surveillance videos.
Journal ArticleDOI
Trajectory based vehicle counting and anomalous event visualization in smart cities
Fozia Mehboob,Fozia Mehboob,Muhammad Abbas,Richard Jiang,Abdul Rauf,Shoab Ahmad Khan,Saad Rehman +6 more
TL;DR: Experimental results demonstrated that proposed pattern detection approach, in comparison with the state of the art algorithms, provides robust vehicle density estimation and event information i.e., lane change information.