Ghazanfar Latif

2.1k citations
83 papers · 1.3k indexed · 1 hit paper · h-index 20
Topics
Brain Tumor Detection and Classification (18 papers)Digital Imaging for Blood Diseases (9 papers)Advanced Neural Network Applications (9 papers)
Journals
SHILAP Revista de lepidopterologíaIEEE AccessApplied Sciences

In The Last Decade

Ghazanfar Latif

77 papers receiving 1.3k citations

Hit Papers

Deep Learning Utilization in Agriculture: Detection of Ri...202220262023202420224080120

Peers

Ghazanfar Latif
Comparison fields: 5 of 113
  • Computer Vision and Pattern Recognition 504
  • Artificial Intelligence 304
  • Radiology, Nuclear Medicine and Imaging 285
  • Neurology 273
  • Human-Computer Interaction 184
Replace Jaafar Alghazo with:
Jaafar Alghazo Saudi Arabia
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Jeongmin Park South Korea
Hamid Tairi Morocco
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Anwer Mustafa Hilal Saudi Arabia
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Ghazanfar Latif relative to Jaafar Alghazo Saudi Arabia Jaafar Alghazo's profile →
Citations per field
00.5×3.7×
Jaafar Alghazo · 1×
Citations per year

Countries citing papers authored by Ghazanfar Latif

Since Specialization
Citations

This map shows the geographic impact of Ghazanfar Latif'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 Ghazanfar Latif with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ghazanfar Latif more than expected).

Fields of papers citing papers by Ghazanfar Latif

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ghazanfar Latif. 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 Ghazanfar Latif. The network helps show where Ghazanfar Latif may publish in the future.

Co-authorship network of co-authors of Ghazanfar Latif

This figure shows the co-authorship network connecting the top 25 collaborators of Ghazanfar Latif. A scholar is included among the top collaborators of Ghazanfar Latif 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 Ghazanfar Latif. Ghazanfar Latif is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 1
4 4
5 2
6 0
7 2
8 1
9 8
10 11
11 48
12 5
13 2
14 82
15 4
16 1
17 90
18 4
19
Multimodal Brain Tumor Segmentation using Neighboring Image Features
6
20
Classification and segmentation of brain tumor using texture analysis
56

About Ghazanfar Latif

Ghazanfar Latif is a scholar working on Neurology, Computer Vision and Pattern Recognition and Media Technology, having authored 83 papers that have together received 1.3k indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (18 papers), Digital Imaging for Blood Diseases (9 papers) and Advanced Neural Network Applications (9 papers). The work is most often cited by research in Human-Computer Interaction (184 citations), Neurology (273 citations) and Computer Vision and Pattern Recognition (504 citations). Ghazanfar Latif has collaborated with scholars based in Saudi Arabia, United States and Malaysia. Frequent co-authors include Jaafar Alghazo, D. N. F. Awang Iskandar, Nazeeruddin Mohammad, Sherif E. Abdelhamid, Abul Bashar, Ghassen Ben Brahim, M. Arfan Jaffar, Anwar M. Mirza, Fadi N. Sibai and Majid Ali Khan. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Applied Sciences.

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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