Jisha John

459 citations
25 papers · 284 · h-index 8

Impact in

Papers in

Jisha John

22 papers receiving 257 citations

Peers

Jisha John
Comparison fields: 5 of 69
  • Management Science and Operations Research 74
  • Artificial Intelligence 147
  • Computer Vision and Pattern Recognition 64
  • Signal Processing 29
  • Biophysics 15
Replace Amauri H. Souza with:
Amauri H. Souza Brazil
Khaled Al-Thelaya Qatar
Zehong Yang China
Stijn Vanderlooy Netherlands
Ruqi Zhou China
Lixia Zhang China
Keshou Wu China
Saiji Fu China
Milind M. Mushrif India
Jisha John relative to Amauri H. Souza Brazil Amauri H. Souza's profile →
Citations per field
00.5×4.9×
Amauri H. Souza · 1×
Citations per year

Countries citing papers authored by Jisha John

Since Specialization
Citations

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

Fields of papers citing papers by Jisha John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Jisha John, 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 Jisha John Line = papers co-authored together Jisha John links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007138
2 200824
3 201720
4 201517
5 202116
6 200615
7 202113
8 200411
9 20155
10 20053
11 20053
12
Modeling with Recurrent Neural Networks using Generalized Mean Neuron Model
20053
13
Oxidation of -apocarotenals to -apocarotenoic acids with silver oxide.
19733
14 20172
15 20222
16 20172
17 20141
18 20231
19 20051
20 20161

About Jisha John

Jisha John is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computer Networks and Communications and Control and Systems Engineering, having authored 25 papers that have together received 284 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Advanced Photonic Communication Systems (5 papers), Optical Wireless Communication Technologies (5 papers), Fuzzy Logic and Control Systems (4 papers), Neural Networks and Applications (4 papers), Optical Network Technologies (3 papers), Digital Imaging for Blood Diseases (2 papers) and Brain Tumor Detection and Classification (2 papers). The work is most often cited by research in Management Science and Operations Research (74 citations), Artificial Intelligence (147 citations), Computer Vision and Pattern Recognition (64 citations), Signal Processing (29 citations) and Biophysics (15 citations). Jisha John has collaborated with scholars based in India. Frequent co-authors include Ram Narayan Yadav, Prem Kalra, M. Wilscy, Aswathy Ravikumar, Madhu S. Nair, Bejoy Abraham, P. Ravi Kumar, Himmat Singh, Naresh Kumar and Chandra Prakash Singh. Their work appears in journals such as Surface and Interface Analysis, Applied Soft Computing, Journal of Applied Biomedicine, Optical and Quantum Electronics and International Journal of Modelling and Simulation.

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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