Muhammad Ashfaq Khan

829 total citations · 1 hit paper
14 papers, 571 citations indexed

About

Muhammad Ashfaq Khan is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Muhammad Ashfaq Khan has authored 14 papers receiving a total of 571 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Signal Processing, 5 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in Muhammad Ashfaq Khan's work include Network Security and Intrusion Detection (4 papers), Advanced Malware Detection Techniques (4 papers) and Advanced Image Processing Techniques (3 papers). Muhammad Ashfaq Khan is often cited by papers focused on Network Security and Intrusion Detection (4 papers), Advanced Malware Detection Techniques (4 papers) and Advanced Image Processing Techniques (3 papers). Muhammad Ashfaq Khan collaborates with scholars based in South Korea, Pakistan and Germany. Muhammad Ashfaq Khan's co-authors include Yangwoo Kim, Md. Rezaul Karim, Farah Deeba, Fayaz Ali Dharejo, Xuezhi Wang, Yuanchun Zhou, Yi Du, Julian Fischer, Andreas Friebe and Abdul Ghaffar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Electronics Letters.

In The Last Decade

Muhammad Ashfaq Khan

14 papers receiving 543 citations

Hit Papers

HCRNNIDS: Hybrid Convolut... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. HCRNNIDS: Hybrid Convolutional Recurrent Neural Network-Based Network Intrusion Detection System
    2021 189 citations Muhammad Ashfaq Khan Processes profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Muhammad Ashfaq Khan South Korea 10 363 347 213 53 34 14 571
Soman KP India 8 159 0.4× 233 0.7× 124 0.6× 39 0.7× 41 1.2× 20 424
Fehaid Alqahtani United Kingdom 10 215 0.6× 207 0.6× 136 0.6× 29 0.5× 41 1.2× 18 422
Mohsin Munir Germany 8 233 0.6× 448 1.3× 228 1.1× 67 1.3× 20 0.6× 19 599
Sriram Srinivasan United States 8 219 0.6× 204 0.6× 149 0.7× 34 0.6× 73 2.1× 22 484
Asim Dilawar Bakhshi Pakistan 8 233 0.6× 193 0.6× 132 0.6× 24 0.5× 31 0.9× 26 400
Huazhi Sun China 7 302 0.8× 294 0.8× 181 0.8× 91 1.7× 29 0.9× 15 476
Jie Tong China 7 240 0.7× 356 1.0× 210 1.0× 25 0.5× 29 0.9× 17 548
Mohammed S. Alshehri Saudi Arabia 14 257 0.7× 235 0.7× 139 0.7× 79 1.5× 75 2.2× 62 594
Aydın Çetin Türkiye 8 269 0.7× 309 0.9× 108 0.5× 155 2.9× 51 1.5× 35 679
I. Sumaiya Thaseen India 13 431 1.2× 400 1.2× 235 1.1× 40 0.8× 65 1.9× 29 595

Countries citing papers authored by Muhammad Ashfaq Khan

Since Specialization
Citations

This map shows the geographic impact of Muhammad Ashfaq Khan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Muhammad Ashfaq Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Ashfaq Khan more than expected).

Fields of papers citing papers by Muhammad Ashfaq Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Ashfaq Khan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Muhammad Ashfaq Khan. The network helps show where Muhammad Ashfaq Khan may publish in the future.

Co-authorship network of co-authors of Muhammad Ashfaq Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Ashfaq Khan. A scholar is included among the top collaborators of Muhammad Ashfaq Khan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Muhammad Ashfaq Khan. Muhammad Ashfaq Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Khan, Muhammad Ashfaq, et al.. (2024). Hepatic stellate cells in zone 1 engage in capillarization rather than myofibroblast formation in murine liver fibrosis. Scientific Reports. 14(1). 18840–18840. 12 indexed citations
2.
Khan, Muhammad Ashfaq & Yangwoo Kim. (2021). Cardiac Arrhythmia Disease Classification Using LSTM Deep Learning Approach. Computers, materials & continua/Computers, materials & continua (Print). 67(1). 427–443. 41 indexed citations
3.
Arfeen, Zeeshan Ahmad, et al.. (2021). Novel Supervisory Management Scheme of Hybrid Sun Empowered Grid-Assisted Microgrid for Rapid Electric Vehicles Charging Area. Applied Sciences. 11(19). 9118–9118. 2 indexed citations
4.
Dharejo, Fayaz Ali, Yuanchun Zhou, Farah Deeba, et al.. (2021). A deep hybrid neural network for single image dehazing via wavelet transform. Optik. 231. 166462–166462. 23 indexed citations
5.
Deeba, Farah, Yuanchun Zhou, Fayaz Ali Dharejo, et al.. (2021). A plexus‐convolutional neural network framework for fast remote sensing image super‐resolution in wavelet domain. IET Image Processing. 15(8). 1679–1687. 10 indexed citations
6.
Khan, Muhammad Ashfaq, Fayaz Ali Dharejo, Farah Deeba, et al.. (2021). Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing. Electronics Letters. 57(11). 436–438. 11 indexed citations
7.
Khan, Muhammad Ashfaq. (2021). HCRNNIDS: Hybrid Convolutional Recurrent Neural Network-Based Network Intrusion Detection System. Processes. 9(5). 834–834. 189 indexed citations breakdown →
8.
Khan, Muhammad Ashfaq & Yangwoo Kim. (2021). Deep Learning-Based Hybrid Intelligent Intrusion Detection System. Computers, materials & continua/Computers, materials & continua (Print). 68(1). 671–687. 34 indexed citations
9.
Usman, Muhammad Arslan, Muhammad Rehan Usman, Gandeva Bayu Satrya, et al.. (2021). QI-BRiCE: Quality Index for Bleeding Regions in Capsule Endoscopy Videos. Computers, materials & continua/Computers, materials & continua (Print). 67(2). 1697–1712. 3 indexed citations
10.
Khan, Muhammad Ashfaq, et al.. (2020). Toward Developing Efficient Conv-AE-Based Intrusion Detection System Using Heterogeneous Dataset. Electronics. 9(11). 1771–1771. 73 indexed citations
11.
Khan, Muhammad Ashfaq, Md. Rezaul Karim, & Yangwoo Kim. (2019). A Scalable and Hybrid Intrusion Detection System Based on the Convolutional-LSTM Network. Symmetry. 11(4). 583–583. 123 indexed citations
12.
Khan, Muhammad Ashfaq, Md. Rezaul Karim, & Yangwoo Kim. (2018). A Two-Stage Big Data Analytics Framework with Real World Applications Using Spark Machine Learning and Long Short-Term Memory Network. Symmetry. 10(10). 485–485. 40 indexed citations
13.
Khan, Muhammad Ashfaq, et al.. (2013). Hepatic Stellate Cells in the Context of Liver Fibrosis. SHILAP Revista de lepidopterología. 1 indexed citations
14.
Hussain, Javid, et al.. (2012). Phytomedicinal Studies of Kurram Agency in the Federally Administered Tribal Areas (FATA) of Pakistan. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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