N Manohar

528 citations
43 papers · 228 indexed · h-index 10
Topics
Vehicle License Plate Recognition (8 papers)Video Surveillance and Tracking Methods (7 papers)Handwritten Text Recognition Techniques (6 papers)
Partner nations
IndiaChinaUnited States

In The Last Decade

N Manohar

33 papers receiving 212 citations

Peers

N Manohar
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 98
  • Artificial Intelligence 44
  • Plant Science 43
  • Media Technology 28
  • Analytical Chemistry 24
Replace Zhenping Qiang with:
Zhenping Qiang China
Sanaa El Fkihi Morocco
Moch Arief Soeleman Indonesia
Vladimir Y. Mariano Philippines
N. Shobha Rani India
Novanto Yudistira Indonesia
Anwar Ur Rehman Italy
Rongyu Zhang China
Qiang Lü China
Dewi Nasien Indonesia
N Manohar relative to Zhenping Qiang China Zhenping Qiang's profile →
Citations per field
00.5×1.6×
Zhenping Qiang · 1×
Citations per year

Countries citing papers authored by N Manohar

Since Specialization
Citations

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

Fields of papers citing papers by N Manohar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N Manohar

This figure shows the co-authorship network connecting the top 25 collaborators of N Manohar. A scholar is included among the top collaborators of N Manohar 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 N Manohar. N Manohar 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
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2 4
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8 0
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10 3
11 7
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13 9
14 6
15 12
16
Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification.
5
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18 7
19 0
20 4

About N Manohar

N Manohar is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Analytical Chemistry, having authored 43 papers that have together received 228 indexed citations. Recurring topics across this work include Vehicle License Plate Recognition (8 papers), Video Surveillance and Tracking Methods (7 papers) and Handwritten Text Recognition Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (98 citations), Media Technology (28 citations) and Analytical Chemistry (24 citations). N Manohar has collaborated with scholars based in India, China and United States. Frequent co-authors include Atul Prakash, N. Shobha Rani, B R Pushpa, G. Hemantha Kumar, S Akshay, M. Willebeek-LeMair, Earlence Fernandes, M. Naghshineh, Jiefeng Chen and Somesh Jha. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and SAE technical papers on CD-ROM/SAE technical paper series.

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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