Smith K. Khare

2.9k citations
43 papers · 1.8k indexed · 4 hit papers · h-index 26
Topics
EEG and Brain-Computer Interfaces (31 papers)ECG Monitoring and Analysis (14 papers)Blind Source Separation Techniques (10 papers)
Partner nations
IndiaDenmarkAustralia

In The Last Decade

Smith K. Khare

42 papers receiving 1.8k citations

Hit Papers

Time–Frequency Representation and Convolutional Neural Ne...2020202620222024202020232023202350100150200

Peers

Smith K. Khare
Comparison fields: 5 of 129
  • Cognitive Neuroscience 1.2k
  • Cardiology and Cardiovascular Medicine 461
  • Experimental and Cognitive Psychology 434
  • Signal Processing 304
  • Artificial Intelligence 263
Replace Enas Abdulhay with:
Enas Abdulhay Jordan
Rajamanickam Yuvaraj Singapore
Nidal Kamel Malaysia
Chen Chen China
Jordi Solé‐Casals Spain
Luay Fraiwan Jordan
Rifai Chai Australia
Manish Sharma India
Zhiguo Zhang China
Martin Glasstetter Germany
Smith K. Khare relative to Enas Abdulhay Jordan Enas Abdulhay's profile →
Citations per field
00.5×3.4×
Enas Abdulhay · 1×
Citations per year

Countries citing papers authored by Smith K. Khare

Since Specialization
Citations

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

Fields of papers citing papers by Smith K. Khare

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Smith K. Khare. 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 Smith K. Khare. The network helps show where Smith K. Khare may publish in the future.

Co-authorship network of co-authors of Smith K. Khare

This figure shows the co-authorship network connecting the top 25 collaborators of Smith K. Khare. A scholar is included among the top collaborators of Smith K. Khare 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 Smith K. Khare. Smith K. Khare 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 2
3 4
4 1
5 8
6 24
7 5
8 7
9 35
10
An explainable and interpretable model for attention deficit hyperactivity disorder in children using EEG signalsbreakdown →
68
11 27
12 8
13 48
14 38
15 17
16 6
17 27
18 35
19 27
20 44

About Smith K. Khare

Smith K. Khare is a scholar working on Cognitive Neuroscience, Signal Processing and Cardiology and Cardiovascular Medicine, having authored 43 papers that have together received 1.8k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (31 papers), ECG Monitoring and Analysis (14 papers) and Blind Source Separation Techniques (10 papers). The work is most often cited by research in Cognitive Neuroscience (1.2k citations), Experimental and Cognitive Psychology (434 citations) and Signal Processing (304 citations). Smith K. Khare has collaborated with scholars based in India, Denmark and Australia. Frequent co-authors include Varun Bajaj, U. Rajendra Acharya, Victoria Blanes‐Vidal, Esmaeil S. Nadimi, G. R. Sinha, Siuly Siuly, Hua Wang, Yanchun Zhang, Vikram M. Gadre and Sachin Taran. Their work appears in journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

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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