G. Sreenu

447 citations
3 papers · 265 indexed · 1 hit paper · h-index 3
Topics
Anomaly Detection Techniques and Applications (2 papers)Video Surveillance and Tracking Methods (2 papers)Fire Detection and Safety Systems (2 papers)
Journals
SHILAP Revista de lepidopterologíaJournal Of Big Data
Partner nations
India

In The Last Decade

G. Sreenu

3 papers receiving 244 citations

Hit Papers

Intelligent video surveillance: a review through deep lea...2019202620212023201950100150200250

Peers

G. Sreenu
Comparison fields: 5 of 69
  • Computer Vision and Pattern Recognition 180
  • Artificial Intelligence 114
  • Computer Networks and Communications 31
  • Safety, Risk, Reliability and Quality 23
  • Signal Processing 20
Replace Amira Ben Mabrouk with:
Amira Ben Mabrouk United States
Mohammed Alatiyyah Saudi Arabia
Jorge García Spain
Hajer Fradi France
Chandrashekar M Patil India
K. Deepak India
Oluwatoyin P. Popoola Nigeria
Aidan Murphy Ireland
Nick C. Tang Taiwan
Xiaodong Yu China
G. Sreenu relative to Amira Ben Mabrouk United States Amira Ben Mabrouk's profile →
Citations per field
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Amira Ben Mabrouk · 1×
Citations per year

Countries citing papers authored by G. Sreenu

Since Specialization
Citations

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

Fields of papers citing papers by G. Sreenu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Sreenu

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

All Works

3 of 3 papers shown
#WorkIndexed citations
1 2
2
Intelligent video surveillance: a review through deep learning techniques for crowd analysisbreakdown →
260
3 3

About G. Sreenu

G. Sreenu is a scholar working on Software, Safety, Risk, Reliability and Quality and Computer Vision and Pattern Recognition, having authored 3 papers that have together received 265 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (2 papers), Video Surveillance and Tracking Methods (2 papers) and Fire Detection and Safety Systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (180 citations), Artificial Intelligence (114 citations) and Safety, Risk, Reliability and Quality (23 citations). G. Sreenu has collaborated with scholars based in India. Frequent co-authors include M.A. Saleem Durai. Their work appears in journals such as SHILAP Revista de lepidopterología and Journal Of Big Data.

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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