Ghulam Ali

1.4k citations
42 papers · 811 indexed · 1 hit paper · h-index 15

Ghulam Ali

40 papers receiving 755 citations

Hit Papers

A Hybrid Convolutional Neural Network Model for Automatic...672023202620242025204060

Peers

Ghulam Ali
Comparison fields: 5 of 113
  • Neurology 95
  • Computer Vision and Pattern Recognition 213
  • Health Information Management 39
  • Health Informatics 10
  • Analytical Chemistry 68
Replace Xianqing Chen with:
Xianqing Chen China
Sultan Alfarhood Saudi Arabia
Qinghua Zhou China
Avinash Sharma India
Jwan Najeeb Saeed Iraq
V. Muneeswaran India
Chirag Patel India
Igi Ardiyanto Indonesia
Paul Trundle United Kingdom
Haza Nuzly Abdull Hamed Malaysia
Ghulam Ali relative to Xianqing Chen China Xianqing Chen's profile →
Citations per field
00.5×7.5×
Xianqing Chen · 1×
Citations per year

Countries citing papers authored by Ghulam Ali

Since Specialization
Citations

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

Fields of papers citing papers by Ghulam Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Ghulam Ali, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ghulam Ali Line = papers co-authored together Ghulam Ali links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202516
3 20251
4 20252
5 20243
6 20242
7 20243
8 20247
9 202324
10 202311
11 202323
12 202211
13 202236
14 202228
15 2021132
16 20206
17 20127
18
Efficient irrigation water management using cost effective wireless sensor and actuator networks
20112
19 20101
20 20105

About Ghulam Ali

Ghulam Ali is a scholar working on Health Informatics, Neurology and Computer Vision and Pattern Recognition, having authored 42 papers that have together received 811 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (5 papers), Multi-Agent Systems and Negotiation (4 papers), Emotion and Mood Recognition (4 papers), Face and Expression Recognition (4 papers), AI in cancer detection (4 papers), Digital Imaging for Blood Diseases (2 papers), Medical Image Segmentation Techniques (2 papers) and Acoustic Wave Resonator Technologies (2 papers). The work is most often cited by research in Neurology (95 citations), Computer Vision and Pattern Recognition (213 citations) and Health Information Management (39 citations). Ghulam Ali has collaborated with scholars based in Pakistan, Saudi Arabia and China. Frequent co-authors include Javed Rashid, Mohammed A. Al Ghamdi, Sultan H. Almotiri, Khalid Masood, Imran Khan, Muhammad Waseem Iqbal, Muhammad Anwar, Tariq Ali, Muhammad Iqbal and Tamim Alkhalifah. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and PLoS ONE.

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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