most citedEnhancing Wrist Fracture Detection with YOLO

66 citations · 80 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20242 cited

Navigating limitations with precision: A fine-grained ensemble approach to wrist pathology recognition on a limited x-ray dataset

Ammar Ahmed, Ali Shariq Imran, Mohib Ullah +2

The exploration of automated wrist fracture recognition has gained considerable research attention in recent years. In practical medical scenarios, physicians and surgeons may lack…

cs.CV20244 cited

Learning from the few: Fine-grained approach to pediatric wrist pathology recognition on a limited dataset

Ammar Ahmed, Ali Shariq Imran, Zenun Kastrati +3

Wrist pathologies, {particularly fractures common among children and adolescents}, present a critical diagnostic challenge. While X-ray imaging remains a prevalent diagnostic tool,…

cs.CV202466 cited

Enhancing Wrist Fracture Detection with YOLO

Ammar Ahmed, Ali Shariq Imran, Abdul Manaf +2

Diagnosing and treating abnormalities in the wrist, specifically distal radius, and ulna fractures, is a crucial concern among children, adolescents, and young adults, with a highe…

cs.SI20208 cited

Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning -- a Case Study on COVID-19

Ali Shariq Imran, Sher Mohammad Doudpota, Zenun Kastrati +1

How different cultures react and respond given a crisis is predominant in a society's norms and political will to combat the situation. Often the decisions made are necessitated by…

cs.CV2020

Kalman Filter Based Multiple Person Head Tracking

Mohib Ullah, Maqsood Mahmud, Habib Ullah +3

For multi-target tracking, target representation plays a crucial rule in performance. State-of-the-art approaches rely on the deep learning-based visual representation that gives a…