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Muhammad Zubair Asghar
ResearcherPublications, citations & collaboration network
Muhammad Zubair Asghar is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 106 works, 1,988 citations, an h-index of 24 and an i10-index of 44.
106
Works
1,988
Citations
24
h-index
44
i10-index
How has Muhammad Zubair Asghar's publication output changed over time?
ScholarIQpublication output · 2014–2023
Output declined50% over the shown period — from 2 works in 2014 to 1 in 2023.
2
1
1
1
2
2
1
2014201520162019202020212023
What are the most-cited papers on Muhammad Zubair Asghar?
ScholarIQmost cited works
Automatic Detection of Citrus Fruit and Leaves Diseases Using Deep Neural Network Model
Asad Masood Khattak, Muhammad Usama Asghar, Ulfat Batool, Muhammad Zubair Asghar, Hayat Ullah, Mabrook Al‐Rakhami, Abdu Gumaei
IEEE Access. 2021240 CitationsOPEN ACCESS
Detection and classification of social media-based extremist affiliations using sentiment analysis techniques
Shakeel Ahmad, Muhammad Zubair Asghar, Fahad Alotaibi, Irfan‐Ullah Awan
S2497168432. 2019169 CitationsOPEN ACCESS
A Review of Feature Extraction in Sentiment Analysis
Muhammad Zubair Asghar, Irfan Ullah Khan, Shakeel Ahmad, Fazal Masud Kundi
2014121 Citations
<scp>Senti‐eSystem</scp>: A sentiment‐based <scp>eSystem</scp>‐using hybridized fuzzy and deep neural network for measuring customer satisfaction
Muhammad Zubair Asghar, Fazli Subhan, Hussain Ahmad, Wazir Zada Khan, Saqib Hakak, Thippa Reddy Gadekallu, Mamoun Alazab
S122199241. 202081 Citations
A Hybrid Deep Learning Technique for Personality Trait Classification From Text
Hussain Al-Ahmad, Muhammad Zubair Asghar, Muhammad Zubair Asghar, Aurangzeb Khan, Amir Mosavi
IEEE Access. 202176 CitationsOPEN ACCESS
Related on ScholarIQ
Gomal University
Institution
Automatic Detection of Citrus Fruit and Leaves Diseases Using Deep Neural Network Model
Paper
Detection and classification of social media-based extremist affiliations using sentiment analysis techniques
Paper
A Review of Feature Extraction in Sentiment Analysis
Paper
<scp>Senti‐eSystem</scp>: A sentiment‐based <scp>eSystem</scp>‐using hybridized fuzzy and deep neural network for measuring customer satisfaction
Paper
A Hybrid Deep Learning Technique for Personality Trait Classification From Text
Paper