44 citations · 117 across the 10 of their papers we have counts for
11 papers
Beyond Pixel Similarity: Task-Aware Evaluation of GAN-Based Synthetic Sonar Data for Robotic Perception
Hannan Ejaz Keen, Muhammad Moazam Fraz, Karsten Berns
Synthetic data can reduce the cost of collecting and annotating training data for robotic perception, but generating sensor observations that preserve the characteristics relevant…
V-SenseDrive: A Privacy-Preserving Road Video and In-Vehicle Sensor Fusion Framework for Road Safety & Driver Behaviour Modelling
Muhammad Naveed, Nazia Perwaiz, Sidra Sultana +2
Road traffic accidents remain a major public health challenge, particularly in countries with heterogeneous road conditions, mixed traffic flow, and variable driving discipline, su…
'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…
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…
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
Saad Wazir, Muhammad Moazam Fraz
Medical image segmentation assists in computer-aided diagnosis, surgeries, and treatment. Digitize tissue slide images are used to analyze and segment glands, nuclei, and other bio…
Nuclei & Glands Instance Segmentation in Histology Images: A Narrative Review
Esha Sadia Nasir, Arshi Perviaz, Muhammad Moazam Fraz
Instance segmentation of nuclei and glands in the histology images is an important step in computational pathology workflow for cancer diagnosis, treatment planning and survival an…