Salem Alelyani

2.7k citations
35 papers · 1.7k indexed · 2 hit papers · h-index 18
Topics
Face and Expression Recognition (7 papers)Complex Network Analysis Techniques (4 papers)Online Learning and Analytics (3 papers)
Journals
SHILAP Revista de lepidopterologíaComputers in Human BehaviorSensors

In The Last Decade

Salem Alelyani

34 papers receiving 1.6k citations

Hit Papers

Feature selection for classification: A review201420262018202220142019100200300400500

Peers

Salem Alelyani
Comparison fields: 5 of 152
  • Artificial Intelligence 743
  • Computer Science Applications 314
  • Computer Vision and Pattern Recognition 272
  • Information Systems 248
  • Computer Networks and Communications 155
Replace Kwok Tai Chui with:
Kwok Tai Chui Hong Kong
Ioannis Hatzilygeroudis Greece
Muna Al‐Razgan Saudi Arabia
Vicente García‐Díaz Spain
Mohammad Shorfuzzaman Saudi Arabia
Haoyi Xiong China
Gustavo Ramírez-González Colombia
Inam Ullah China
Giovanni Acampora Italy
Salem Alelyani relative to Kwok Tai Chui Hong Kong Kwok Tai Chui's profile →
Citations per field
00.5×1.5×2.3×
Kwok Tai Chui · 1×
Citations per year

Countries citing papers authored by Salem Alelyani

Since Specialization
Citations

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

Fields of papers citing papers by Salem Alelyani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salem Alelyani

This figure shows the co-authorship network connecting the top 25 collaborators of Salem Alelyani. A scholar is included among the top collaborators of Salem Alelyani 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 Salem Alelyani. Salem Alelyani 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 46
2 6
3 5
4 0
5 51
6 32
7 27
8 29
9 1
10 7
11 22
12 114
13 9
14 29
15 1
16 167
17
Feature selection for classification: A reviewbreakdown →
560
18 2
19 2
20 29

About Salem Alelyani

Salem Alelyani is a scholar working on Health Informatics, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 1.7k indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), Complex Network Analysis Techniques (4 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Computer Science Applications (314 citations), Health Informatics (48 citations) and Health Information Management (121 citations). Salem Alelyani has collaborated with scholars based in Saudi Arabia, Pakistan and United States. Frequent co-authors include Jiliang Tang, Huan Liu, Saeed‐Ul Hassan, Naif Radi Aljohani, Raheel Nawaz, Hajra Waheed, Huan Liu, Julie Hardman, Mohamed Mohana and Nor Azlina Ab. Aziz. Their work appears in journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and Sensors.

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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