5 citations · 9 across the 2 of their papers we have counts for
2 papers
eess.IV2023★ 5 cited
'Aariz: A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification
Muhammad Anwaar Khalid, Kanwal Zulfiqar, Ulfat Bashir +5
The accurate identification and precise localization of cephalometric landmarks enable the classification and quantification of anatomical abnormalities. The traditional way of mar…
cs.CV2022★ 4 cited
CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023
Muhammad Anwaar Khalid, Kanwal Zulfiqar, Ulfat Bashir +5
Quantitative cephalometric analysis is the most widely used clinical and research tool in modern orthodontics. Accurate localization of cephalometric landmarks enables the quantifi…