Amit Suveer

656 total citations
9 papers, 465 citations indexed

About

Amit Suveer is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Biophysics. According to data from OpenAlex, Amit Suveer has authored 9 papers receiving a total of 465 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Media Technology and 3 papers in Biophysics. Recurrent topics in Amit Suveer's work include Image Processing Techniques and Applications (3 papers), Cell Image Analysis Techniques (3 papers) and Advanced Image Processing Techniques (2 papers). Amit Suveer is often cited by papers focused on Image Processing Techniques and Applications (3 papers), Cell Image Analysis Techniques (3 papers) and Advanced Image Processing Techniques (2 papers). Amit Suveer collaborates with scholars based in Sweden, India and Serbia. Amit Suveer's co-authors include Debdoot Sheet, Hrushikesh Garud, Manjunatha Mahadevappa, Jyotirmoy Chatterjee, Ida‐Maria Sintorn, Anindya Gupta, Philip J. Harrison, Kimmo Kartasalo, Anna H. Klemm and Leslie Solorzano and has published in prestigious journals such as BioMed Research International, IEEE Transactions on Consumer Electronics and Cytometry Part A.

In The Last Decade

Amit Suveer

9 papers receiving 441 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Amit Suveer Sweden	6	312	182	73	45	44	9	465
Rodrigo Nava Mexico	9	83 0.3×	125 0.7×	65 0.9×	33 0.7×	52 1.2×	28	311
Yuri Murakami Japan	16	270 0.9×	153 0.8×	48 0.7×	54 1.2×	230 5.2×	65	622
Saad Rizvi China	11	144 0.5×	99 0.5×	21 0.3×	82 1.8×	56 1.3×	20	438
Jeffery R. Price United States	12	185 0.6×	58 0.3×	26 0.4×	60 1.3×	29 0.7×	40	400
Amir Tahmasbi Iran	10	168 0.5×	46 0.3×	53 0.7×	86 1.9×	25 0.6×	18	398
Seungil Huh United States	12	186 0.6×	136 0.7×	226 3.1×	25 0.6×	62 1.4×	20	425
Bert Geelen Belgium	11	174 0.6×	171 0.9×	41 0.6×	38 0.8×	65 1.5×	32	462
Lucio Azzari Finland	10	184 0.6×	85 0.5×	25 0.3×	68 1.5×	22 0.5×	13	328
Jacques Facon Brazil	10	328 1.1×	149 0.8×	7 0.1×	51 1.1×	28 0.6×	48	483
Gabriel Eilertsen Sweden	11	667 2.1×	153 0.8×	18 0.2×	98 2.2×	106 2.4×	27	842

Countries citing papers authored by Amit Suveer

Since Specialization

Citations

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

Fields of papers citing papers by Amit Suveer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amit Suveer

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

All Works

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9 of 9 papers shown

1.

Suveer, Amit, et al.. (2019). Super-Resolution Reconstruction of Transmission Electron Microscopy Images Using Deep Learning. 548–551. 10 indexed citations

2.

Gupta, Anindya, Philip J. Harrison, Håkan Wieslander, et al.. (2018). Deep Learning in Image Cytometry: A Review. Cytometry Part A. 95(4). 366–380. 128 indexed citations

3.

Suveer, Amit, et al.. (2018). Denoising of short exposure transmission electron microscopy images for ultrastructural enhancement. 25. 921–925. 5 indexed citations

4.

Suveer, Amit, Nataša Sladoje, Joakim Lindblad, Anca Dragomir, & Ida‐Maria Sintorn. (2016). Automated detection of cilia in low magnification transmission electron microscopy images using template matching. 60. 386–390. 3 indexed citations

5.

Lindblad, Joakim, Nataša Sladoje, Amit Suveer, Anca Dragomir, & Ida‐Maria Sintorn. (2015). High-resolution reconstruction by feature distance minimization from multiple views of an object. 29–34. 2 indexed citations

6.

Jayadev, Chaitra, Anand Vinekar, Samit Desai, et al.. (2015). Enhancing Image Characteristics of Retinal Images of Aggressive Posterior Retinopathy of Prematurity Using a Novel Software, (RetiView). BioMed Research International. 2015. 1–8. 7 indexed citations

7.

Garud, Hrushikesh, Debdoot Sheet, Amit Suveer, et al.. (2011). Brightness preserving contrast enhancement in digital pathology. 1–5. 13 indexed citations

8.

Sheet, Debdoot, Hrushikesh Garud, Amit Suveer, Manjunatha Mahadevappa, & Jyotirmoy Chatterjee. (2010). Brightness preserving dynamic fuzzy histogram equalization. IEEE Transactions on Consumer Electronics. 56(4). 2475–2480. 296 indexed citations

9.

Sheet, Debdoot, Vikram Venkatraghavan, Amit Suveer, et al.. (2010). Statistical tools for evaluating classification efficacy of feature extraction techniques. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7546. 75461B–75461B. 1 indexed citations

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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