Dipti Deodhare

424 citations
19 papers · 258 · h-index 10

Impact in

Papers in

Dipti Deodhare

17 papers receiving 229 citations

Peers

Dipti Deodhare
Comparison fields: 5 of 65
  • Computer Vision and Pattern Recognition 123
  • Artificial Intelligence 141
  • Media Technology 14
  • Signal Processing 15
  • Automotive Engineering 15
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Chuming Li China
Tianyun Zhang United States
Fucheng You China
José Antonio Martín H. Spain
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Citations per year

Countries citing papers authored by Dipti Deodhare

Since Specialization
Citations

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

Fields of papers citing papers by Dipti Deodhare

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Dipti Deodhare, 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 Dipti Deodhare Line = papers co-authored together Dipti Deodhare links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 200471
2 199833
3
Deep domain adaptation in action space
201830
4
Parallel Levenberg-Marquardt-Based Neural Network Training on Linux Clusters-A Case Study.
200225
5
Preprocessing and Image Enhancement Algorithms for a Form-based Intelligent Character Recognition System
200521
6 201415
7 201514
8 201612
9
Lexical Chains as Document Features
20089
10 20159
11 20126
12 20134
13 20173
14 20063
15 20121
16 20061
17 20141
18 20060
19 20190

About Dipti Deodhare

Dipti Deodhare is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Mechanical Engineering and Signal Processing, having authored 19 papers that have together received 258 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (4 papers), Modular Robots and Swarm Intelligence (4 papers), Neural Networks and Applications (4 papers), Robotics and Sensor-Based Localization (4 papers), Face and Expression Recognition (2 papers), Handwritten Text Recognition Techniques (2 papers), Advanced Neural Network Applications (2 papers) and Advancements in Battery Materials (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (123 citations), Artificial Intelligence (141 citations), Media Technology (14 citations), Signal Processing (15 citations) and Automotive Engineering (15 citations). Dipti Deodhare has collaborated with scholars based in India and United States. Frequent co-authors include Niranjan Suri, Deniz Erdoğmuş, José C. Prı́ncipe, Vikas Sindhwani, Partha Niyogi, M. Vidyasagar, P. Nagabhushan, K. S. Venkatesh, Vinay P. Namboodiri and Deepak Khemani. Their work appears in journals such as Sadhana, IEEE Robotics and Automation Letters, IEEE Intelligent Systems, Bulletin of Materials Science and Infrared Physics & 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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