Amit Kumar Das

1.7k citations
75 papers · 1.1k indexed · h-index 22
Topics
IoT and Edge/Fog Computing (12 papers)Handwritten Text Recognition Techniques (11 papers)Image Retrieval and Classification Techniques (9 papers)

In The Last Decade

Amit Kumar Das

68 papers receiving 1.0k citations

Peers

Amit Kumar Das
Comparison fields: 5 of 117
  • Artificial Intelligence 411
  • Information Systems 329
  • Computer Networks and Communications 211
  • Computer Vision and Pattern Recognition 202
  • Signal Processing 89
Replace Guruh Fajar Shidik with:
Guruh Fajar Shidik Indonesia
Sapna Juneja India
Mohammed A. M. Sadeeq Iraq
Teddy Mantoro Indonesia
Zafer Al-Makhadmeh Saudi Arabia
Muhammad Saleem Pakistan
Salekul Islam Bangladesh
Rajalakshmi Krishnamurthi India
Antonino Galletta Italy
Munish Bhatia India
Amit Kumar Das relative to Guruh Fajar Shidik Indonesia Guruh Fajar Shidik's profile →
Citations per field
00.5×4.7×
Guruh Fajar Shidik · 1×
Citations per year

Countries citing papers authored by Amit Kumar Das

Since Specialization
Citations

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

Fields of papers citing papers by Amit Kumar Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amit Kumar Das. 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 Amit Kumar Das. The network helps show where Amit Kumar Das may publish in the future.

Co-authorship network of co-authors of Amit Kumar Das

This figure shows the co-authorship network connecting the top 25 collaborators of Amit Kumar Das. A scholar is included among the top collaborators of Amit Kumar Das 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 Amit Kumar Das. Amit Kumar Das 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
1 0
2 0
3 1
4 5
5 3
6 72
7 1
8 5
9 45
10 20
11 60
12 33
13 20
14 1
15 4
16 27
17 14
18 1
19
A Very Efficient Table Detection System from Document Images.
1
20
Image Retrieval Using Relevance Feedback Based on Mann-Whitney Test.
1

About Amit Kumar Das

Amit Kumar Das is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Health Information Management, having authored 75 papers that have together received 1.1k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (12 papers), Handwritten Text Recognition Techniques (11 papers) and Image Retrieval and Classification Techniques (9 papers). The work is most often cited by research in Information Systems (329 citations), Artificial Intelligence (411 citations) and Computer Vision and Pattern Recognition (202 citations). Amit Kumar Das has collaborated with scholars based in Bangladesh, India and South Korea. Frequent co-authors include Md. Abdur Razzaque, Tamal Adhikary, Bhabatosh Chanda, Choong Seon Hong, Mohammad Mehedi Hassan, Majed Alrubaian, Sharif Ahmed, Md. Asaduzzaman, Md. Nazmul Hasan and Ahmad Almogren. Their work appears in journals such as Frontiers in Plant Science, Applied Sciences and Naunyn-Schmiedeberg s Archives of Pharmacology.

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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