Kelwin Fernandes

944 total citations
18 papers, 270 citations indexed

About

Kelwin Fernandes is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Kelwin Fernandes has authored 18 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Kelwin Fernandes's work include Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (4 papers) and AI in cancer detection (3 papers). Kelwin Fernandes is often cited by papers focused on Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (4 papers) and AI in cancer detection (3 papers). Kelwin Fernandes collaborates with scholars based in Portugal, Venezuela and Denmark. Kelwin Fernandes's co-authors include Jaime S. Cardoso, Davide Chicco, Joaquim Pinto da Costa, Luís F. Teixeira, Birgitte Schmidt Astrup, Pedro Silva, Manuel Ricardo, Héctor Palacios, Rui Campos and Francisco J. Andrade and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Access and Neurocomputing.

In The Last Decade

Kelwin Fernandes

18 papers receiving 261 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kelwin Fernandes Portugal 9 168 52 46 37 33 18 270
Kung-Min Wang Taiwan 5 133 0.8× 16 0.3× 14 0.3× 5 0.1× 63 1.9× 7 206
Fahima A. Maghraby Egypt 8 138 0.8× 20 0.4× 27 0.6× 3 0.1× 43 1.3× 22 233
Hamzeh Asgharnezhad Australia 6 125 0.7× 28 0.5× 34 0.7× 3 0.1× 14 0.4× 8 249
Terence A. Etchells United Kingdom 10 139 0.8× 9 0.2× 23 0.5× 4 0.1× 23 0.7× 23 325
Ahmad S. Tarawneh Jordan 6 89 0.5× 10 0.2× 29 0.6× 6 0.2× 22 0.7× 11 202
B. Sai Chandana India 8 83 0.5× 8 0.2× 92 2.0× 6 0.2× 7 0.2× 38 216
Huiqi Deng China 6 178 1.1× 7 0.1× 23 0.5× 4 0.1× 14 0.4× 7 338
Sohaib Asif China 10 84 0.5× 26 0.5× 48 1.0× 2 0.1× 19 0.6× 18 235
Renjun Shuai China 8 153 0.9× 36 0.7× 140 3.0× 5 0.1× 13 0.4× 10 301
Ferhat Bozkurt Türkiye 11 122 0.7× 10 0.2× 119 2.6× 3 0.1× 17 0.5× 38 288

Countries citing papers authored by Kelwin Fernandes

Since Specialization
Citations

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

Fields of papers citing papers by Kelwin Fernandes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kelwin Fernandes

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

All Works

18 of 18 papers shown
1.
Fernandes, Kelwin, et al.. (2020). Understanding the decisions of CNNs: An in-model approach. Pattern Recognition Letters. 133. 373–380. 17 indexed citations
2.
Fernandes, Kelwin, et al.. (2019). Sparse Multi-Bending Snakes. IEEE Transactions on Image Processing. 28(8). 3898–3909. 1 indexed citations
3.
Fernandes, Kelwin, et al.. (2019). A Machine Learning Based Quality of Service Estimator for Aerial Wireless Networks. 1–6. 7 indexed citations
4.
Fernandes, Kelwin, et al.. (2019). How to produce complementary explanations using an Ensemble Model. 1–8. 10 indexed citations
5.
Fernandes, Kelwin, et al.. (2019). Directional Support Vector Machines. Applied Sciences. 9(4). 725–725. 4 indexed citations
6.
Fernandes, Kelwin, et al.. (2019). Quality-based Regularization for Iterative Deep Image Segmentation. PubMed. 2019. 6734–6737. 2 indexed citations
7.
Fernandes, Kelwin, et al.. (2018). Automated Methods for the Decision Support of Cervical Cancer Screening Using Digital Colposcopies. IEEE Access. 6. 33910–33927. 45 indexed citations
8.
Fernandes, Kelwin, Jaime S. Cardoso, & Birgitte Schmidt Astrup. (2018). A deep learning approach for the forensic evaluation of sexual assault. Pattern Analysis and Applications. 21(3). 629–640. 8 indexed citations
9.
Fernandes, Kelwin, et al.. (2018). Binary ranking for ordinal class imbalance. Pattern Analysis and Applications. 21(4). 931–939. 3 indexed citations
10.
Fernandes, Kelwin, et al.. (2018). Deep Image Segmentation by Quality Inference. 10. 1–8. 9 indexed citations
11.
Fernandes, Kelwin, et al.. (2018). Supervised deep learning embeddings for the prediction of cervical cancer diagnosis. PeerJ Computer Science. 4. e154–e154. 64 indexed citations
12.
Fernandes, Kelwin & Jaime S. Cardoso. (2018). Ordinal Image Segmentation using Deep Neural Networks. 1–7. 5 indexed citations
13.
Fernandes, Kelwin & Jaime S. Cardoso. (2017). Hypothesis transfer learning based on structural model similarity. Neural Computing and Applications. 31(8). 3417–3430. 14 indexed citations
14.
Fernandes, Kelwin, et al.. (2016). Tackling class imbalance with ranking. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 2182–2187. 25 indexed citations
15.
Fernandes, Kelwin, Jaime S. Cardoso, & Héctor Palacios. (2016). Learning and ensembling lexicographic preference trees with multiple kernels. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 14. 2140–2147. 3 indexed citations
16.
Fernandes, Kelwin & Jaime S. Cardoso. (2016). Discriminative directional classifiers. Neurocomputing. 207. 141–149. 7 indexed citations
17.
Fernandes, Kelwin, et al.. (2015). Random Forest with Increased Generalization: A Universal Background Approach for Authorship Verification.. CLEF (Working Notes). 10 indexed citations
18.
Fernandes, Kelwin, et al.. (2014). Pavement pathologies classification using graph-based features. 793–797. 36 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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