M
Muhammad Aksam Iftikhar
Researcher at COMSATS Institute of Information Technology
Publications - 38
Citations - 1011
Muhammad Aksam Iftikhar is an academic researcher from COMSATS Institute of Information Technology. The author has contributed to research in topics: Segmentation & Feature selection. The author has an hindex of 11, co-authored 35 publications receiving 692 citations. Previous affiliations of Muhammad Aksam Iftikhar include Pakistan Institute of Engineering and Applied Sciences.
Papers
More filters
Journal ArticleDOI
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
TL;DR: The studies reviewed indicate that the classification frameworks formulated on the basis of these features show promise for individualized diagnosis and prediction of clinical progression, and a detailed account of AD classification challenges is provided.
Journal ArticleDOI
Ensemble classification of colon biopsy images based on information rich hybrid features
TL;DR: A colon biopsy image classification system, called CBIC, which benefits from discriminatory capabilities of information rich hybrid feature spaces, and performance enhancement based on ensemble classification methodology, and an ensemble classifier based on majority voting has been proposed.
Journal ArticleDOI
A review of retinal blood vessels extraction techniques: challenges, taxonomy, and future trends
Khan Bahadar Khan,Khan Bahadar Khan,Amir A. Khaliq,Abdul Jalil,Muhammad Aksam Iftikhar,Najeeb Ullah,Muhammad Waqar Aziz,Kifayat Ullah,Muhammad Shahid +8 more
TL;DR: This survey presents a comprehensive review of several automatic retinal vessels extraction techniques, strategies, and algorithms presented to date and separates them into logical groups based on the underlying methodology employed for retinal vessel extraction.
Journal ArticleDOI
Role of Hybrid Deep Neural Networks (HDNNs), Computed Tomography, and Chest X-rays for the Detection of COVID-19.
Muhammad Irfan,Muhammad Aksam Iftikhar,Sana Yasin,Umar Draz,Tariq Ali,Shafiq Hussain,Sarah Bukhari,Abdullah S. Alwadie,Saifur Rahman,Adam Glowacz,Faisal Althobiani +10 more
TL;DR: In this paper, a hybrid deep neural network (HDNN) was proposed to predict the risk of the onset of disease in patients suffering from COVID-19, where the subjects were classified into 3 categories namely normal, pneumonia, and COVID19.
Journal ArticleDOI
Visual object tracking--classical and contemporary approaches
Ahmad Ali,Abdul Jalil,Jianwei Niu,Xiaoke Zhao,Saima Rathore,Javed Ahmed,Muhammad Aksam Iftikhar +6 more
TL;DR: This article introduces the readers to VOT and its applications in other domains, different issues which arise in it, various classical as well as contemporary approaches for object tracking, 4) evaluation methodologies for VOT, and 5) online resources, i.e., annotated datasets and source code available for various tracking techniques.