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pro vyhledávání: '"Waseem, Muhammad Ahmad"'
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 recent advancements in deep learning have made great strides in autom
Externí odkaz:
http://arxiv.org/abs/2311.02617
Autor:
Awan, Mamona, Khan, Muhammad Haris, Baliah, Sanoojan, Waseem, Muhammad Ahmad, Khan, Salman, Khan, Fahad Shahbaz, Mahmood, Arif
We study a challenging problem of unsupervised discovery of object landmarks. Many recent methods rely on bottlenecks to generate 2D Gaussian heatmaps however, these are limited in generating informed heatmaps while training, presumably due to the la
Externí odkaz:
http://arxiv.org/abs/2309.10518
Autor:
Rahman, Muhammad Abdul, Waseem, Muhammad Ahmad, Khalid, Zubair, Tahir, Muhammad, Uppal, Momin
Any policy-level decision-making procedure and academic research involving the optimum use of resources for development and planning initiatives depends on accurate population density statistics. The current cutting-edge datasets offered by WorldPop
Externí odkaz:
http://arxiv.org/abs/2307.16084
Autor:
Nazir, Usman, Waseem, Muhammad Ahmad, Khan, Falak Sher, Saeed, Rabia, Hasan, Syed Muhammad, Uppal, Momin, Khalid, Zubair
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 provides a means of extended availability and enhanced reliability of flood
Externí odkaz:
http://arxiv.org/abs/2306.06074