3 citations · 6 across the 15 of their papers we have counts for
8 papers · 1 filter
TFNet: Tuning Fork Network with Neighborhood Pixel Aggregation for Improved Building Footprint Extraction
Muhammad Ahmad Waseem, Muhammad Tahir, Zubair Khalid +1
This paper considers the problem of extracting building footprints from satellite imagery -- a task that is critical for many urban planning and decision-making applications. While…
Logistics Hub Location Optimization: A K-Means and P-Median Model Hybrid Approach Using Road Network Distances
Muhammad Abdul Rahman, Muhammad Aamir Basheer, Zubair Khalid +2
Logistic hubs play a pivotal role in the last-mile delivery distance; even a slight increment in distance negatively impacts the business of the e-commerce industry while also incr…
PD-SEG: Population Disaggregation Using Deep Segmentation Networks For Improved Built Settlement Mask
Muhammad Abdul Rahman, Muhammad Ahmad Waseem, Zubair Khalid +2
Any policy-level decision-making procedure and academic research involving the optimum use of resources for development and planning initiatives depends on accurate population dens…
EMORF/S: EM-Based Outlier-Robust Filtering and Smoothing With Correlated Measurement Noise
Aamir Hussain Chughtai, Muhammad Tahir, Momin Uppal
In this article, we consider the problem of outlier-robust state estimation where the measurement noise can be correlated. Outliers in data arise due to many reasons like sensor ma…
STEF-DHNet: Spatiotemporal External Factors Based Deep Hybrid Network for Enhanced Long-Term Taxi Demand Prediction
Sheraz Hassan, Muhammad Tahir, Momin Uppal +3
Accurately predicting the demand for ride-hailing services can result in significant benefits such as more effective surge pricing strategies, improved driver positioning, and enha…
Improved flood mapping for efficient policy design by fusion of Sentinel-1, Sentinel-2, and Landsat-9 imagery to identify population and infrastructure exposed to floods
Usman Nazir, Muhammad Ahmad Waseem, Falak Sher Khan +4
A reliable yet inexpensive tool for the estimation of flood water spread is conducive for efficient disaster management. The application of optical and SAR imagery in tandem provid…
Feature Selection on Sentinel-2 Multi-spectral Imagery for Efficient Tree Cover Estimation
Usman Nazir, Momin Uppal, Muhammad Tahir +1
This paper proposes a multi-spectral random forest classifier with suitable feature selection and masking for tree cover estimation in urban areas. The key feature of the proposed…
Mitigating climate and health impact of small-scale kiln industry using multi-spectral classifier and deep learning
Usman Nazir, Murtaza Taj, Momin Uppal +1
Industrial air pollution has a direct health impact and is a major contributor to climate change. Small scale industries particularly bull-trench brick kilns are one of the key sou…