Deepa Jose

518 citations
31 papers · 282 · h-index 7

Impact in

Papers in

Deepa Jose

26 papers receiving 256 citations

Peers

Deepa Jose
Comparison fields: 5 of 64
  • Signal Processing 61
  • Computer Networks and Communications 103
  • Artificial Intelligence 111
  • Information Systems 62
  • Plant Science 64
Replace L. SaiRamesh with:
L. SaiRamesh India
R. Ramalakshmi India
G. S. Anandha Mala India
Sai Sree Laya Chukkapalli United States
G. Jaspher W. Kathrine India
Mehdi Nafa Algeria
Mohammad Amiri-Zarandi Canada
Amir El-Ghamry Egypt
Nedal Ababneh United Arab Emirates
Monica R. Mundada India
Deepa Jose relative to L. SaiRamesh India L. SaiRamesh's profile →
Citations per field
00.5×
L. SaiRamesh · 1×
Citations per year

Countries citing papers authored by Deepa Jose

Since Specialization
Citations

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

Fields of papers citing papers by Deepa Jose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Deepa Jose, 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 Deepa Jose Line = papers co-authored together Deepa Jose links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202276
2 202261
3 202235
4 201926
5 201820
6 20238
7 20236
8 20236
9 20185
10
Congestion Control in TCP/IP Using Fuzzy Logic
20123
11 20233
12 20203
13 20173
14 20213
15 20153
16
Challenges and Issues in Android App Development- An Overview
20153
17 20243
18 20212
19 20212
20 20132

About Deepa Jose

Deepa Jose is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Signal Processing, having authored 31 papers that have together received 282 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (6 papers), Advanced Malware Detection Techniques (5 papers), AI in cancer detection (4 papers), Brain Tumor Detection and Classification (3 papers), Anomaly Detection Techniques and Applications (3 papers), Chaos-based Image/Signal Encryption (3 papers), IoT and Edge/Fog Computing (3 papers) and Energy Efficient Wireless Sensor Networks (3 papers). The work is most often cited by research in Signal Processing (61 citations), Computer Networks and Communications (103 citations), Artificial Intelligence (111 citations), Information Systems (62 citations) and Plant Science (64 citations). Deepa Jose has collaborated with scholars based in India, Sri Lanka and Australia. Frequent co-authors include Ketan Kotecha, B. Karthik, V. Vijayakumar, Balasubramanian Prabhu Kavin, Pravin R. Kshirsagar, S. Hemalatha, Vineet Tirth, D. R. Singh, Sachi Nandan Mohanty and Minjia Shi. Their work appears in journals such as Wireless Communications and Mobile Computing, Computer Methods in Biomechanics & Biomedical Engineering, Transactions on Emerging Telecommunications Technologies, IEEE Access and International Journal of Information Technology.

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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