Search Results for author:
Found 3 papers, 1 papers with code
'Aariz: A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification
The accurate identification and precise localization of cephalometric landmarks enable the classification and quantification of anatomical abnormalities.
CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023
Quantitative cephalometric analysis is the most widely used clinical and research tool in modern orthodontics.
Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection
Among these algorithms, Vision Transformers are evolved as one of the most contemporary and dominant architectures that are being used in the field of computer vision.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
