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Muhammad Hammad Saleem
ResearcherPublications, citations & collaboration network
Muhammad Hammad Saleem is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 21 works, 1,987 citations, an h-index of 10 and an i10-index of 11.
21
Works
1,987
Citations
10
h-index
11
i10-index
How has Muhammad Hammad Saleem's publication output changed over time?
ScholarIQpublication output · 2015–2025
Output grew0% over the shown period — from 1 works in 2015 to 1 in 2025.
1
1
2
2
4
1
201520192020202120222025
What are the most-cited papers on Muhammad Hammad Saleem?
ScholarIQmost cited works
Plant Disease Detection and Classification by Deep Learning
Muhammad Hammad Saleem, Johan Potgieter, Khalid Mahmood Arif
S4210230202. 2019856 CitationsOPEN ACCESS
Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments
Muhammad Hammad Saleem, Johan Potgieter, Khalid Mahmood Arif
S42419699. 2021414 Citations
Plant Disease Classification: A Comparative Evaluation of Convolutional Neural Networks and Deep Learning Optimizers
Muhammad Hammad Saleem, Johan Potgieter, Khalid Mahmood Arif
S4210230202. 2020258 CitationsOPEN ACCESS
Image-Based Plant Disease Identification by Deep Learning Meta-Architectures
Muhammad Hammad Saleem, Sapna Khanchi, Johan Potgieter, Khalid Mahmood Arif
S4210230202. 2020175 CitationsOPEN ACCESS
A Performance-Optimized Deep Learning-Based Plant Disease Detection Approach for Horticultural Crops of New Zealand
Muhammad Hammad Saleem, Johan Potgieter, Khalid Mahmood Arif
IEEE Access. 2022116 CitationsOPEN ACCESS
Related on ScholarIQ
University of Salford
Institution
Plant Disease Detection and Classification by Deep Learning
Paper
Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments
Paper
Plant Disease Classification: A Comparative Evaluation of Convolutional Neural Networks and Deep Learning Optimizers
Paper
Image-Based Plant Disease Identification by Deep Learning Meta-Architectures
Paper
A Performance-Optimized Deep Learning-Based Plant Disease Detection Approach for Horticultural Crops of New Zealand
Paper