scispace - formally typeset
S

Sajid Anwar

Researcher at Information Technology Institute

Publications -  67
Citations -  2530

Sajid Anwar is an academic researcher from Information Technology Institute. The author has contributed to research in topics: Software system & Deep learning. The author has an hindex of 16, co-authored 67 publications receiving 1862 citations. Previous affiliations of Sajid Anwar include Ghulam Ishaq Khan Institute of Engineering Sciences and Technology & Seoul National University.

Papers
More filters
Journal ArticleDOI

Project scheduling conflict identification and resolution using genetic algorithms (GA)

TL;DR: In this paper, a genetic algorithm based technique for conflict identification and resolution for project activities has been proposed and the effectiveness and utility of such a technique has also been discussed in this paper.
Journal ArticleDOI

Fusion of CNN and sparse representation for threat estimation near power lines and poles infrastructure using aerial stereo imagery

TL;DR: A novel approach based on the fusion of the convolutional neural network (CNN) and sparse representation that handled textureless region, depth discontinuity and smooth region to produce better disparity map that further used for threat estimation using height and distance of vegetation/trees near power lines and poles.
Proceedings ArticleDOI

Compromised User Credentials Detection Using Temporal Features: A Prudent Based Approach

TL;DR: The proposed study presents a novel approach to detect compromised users' activity in a live database that uses a composition of prudence analysis, ripple down rules (RDR), and simulated experts to identify accounts that experience a sudden change in behavior.
Journal ArticleDOI

Behavioral Attestation for Web Services using access policies

TL;DR: A novel framework, Behavioral Attestation for Web Services, in which XACML is built on top of WS-Attestation in order to enable more flexible remote attestation at the web services level and a prototype is presented, which implements XAC ML behavior policy using low-level attestation techniques.
Journal ArticleDOI

Efficient motion estimation using two-bit transform and modified multilevel successive elimination

TL;DR: The speedup in computation as a result of using two-bit transform is rectified by imposing a modified version of multilevel successive elimination algorithm in orthogonal form, which reduces the number of search points in the search window.