A
Asifullah Khan
Researcher at Pakistan Institute of Engineering and Applied Sciences
Publications - 232
Citations - 7325
Asifullah Khan is an academic researcher from Pakistan Institute of Engineering and Applied Sciences. The author has contributed to research in topics: Digital watermarking & Computer science. The author has an hindex of 38, co-authored 192 publications receiving 5109 citations. Previous affiliations of Asifullah Khan include Gwangju Institute of Science and Technology & Ghulam Ishaq Khan Institute of Engineering Sciences and Technology.
Papers
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Proceedings ArticleDOI
Smart Phone Based Online Medicine Authentication Using Print-Cam Robust Watermarking
TL;DR: Experimental results show that the proposed algorithm is robust against print-cam attack and can be used for potential camera based online medicine authentication.
Proceedings ArticleDOI
Feature selection based image clustering using local discriminant model and global integration
TL;DR: This work experimentally observed the enhanced performance of LDMGI algorithm in terms of clustering accuracy and normalized mutual information (NMI) and shows that the effectiveness of this approach could be substantially enhanced with parameter selection and dimensionality reduction approach.
Posted Content
Extracting Signals of Higgs Boson From Background Noise Using Deep Neural Networks.
TL;DR: The proposed ensemble technique is based on achieving diversity in the decision space, and the results show good discrimination power on the private leaderboard; achieving an area under the Receiver Operating Characteristic curve of 0.9 and an Approximate Median Significance score of 3.429.
Proceedings ArticleDOI
Performance improvement in image clustering using local discriminant model and global integration
TL;DR: Improved-LDMGI, a novel image clustering algorithm, has been developed by fine tuning the optimal value of λ in small step size of 0.25 while keeping k = 5 for all image dataset except handwritten image dataset.
Journal ArticleDOI
CB-HVTNet: A channel-boosted hybrid vision transformer network for lymphocyte assessment in histopathological images
TL;DR: In this paper , the authors proposed a Channel Boosted Hybrid Vision Transformer (CB HVT) that uses transfer learning to generate boosted channels and employs both transformers and CNNs to analyse lymphocytes in histopathological images.