Oge Marques

4.0k total citations · 1 hit paper
118 papers, 2.3k citations indexed

About

Oge Marques is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Oge Marques has authored 118 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Computer Vision and Pattern Recognition, 24 papers in Artificial Intelligence and 18 papers in Signal Processing. Recurrent topics in Oge Marques's work include Advanced Image and Video Retrieval Techniques (30 papers), Image Retrieval and Classification Techniques (28 papers) and Video Analysis and Summarization (20 papers). Oge Marques is often cited by papers focused on Advanced Image and Video Retrieval Techniques (30 papers), Image Retrieval and Classification Techniques (28 papers) and Video Analysis and Summarization (20 papers). Oge Marques collaborates with scholars based in United States, Austria and Brazil. Oge Marques's co-authors include Borko Furht, Xingquan Zhu, Xavier Giró-i-Nieto, Mathias Lux, Hari Kalva, Dubravko Ćulibrk, Daniel Socek, Tehreem Syed, Aleksandar Nešković and Branka Stojanović and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Journal of the American Academy of Dermatology.

In The Last Decade

Oge Marques

113 papers receiving 2.1k citations

Hit Papers

Dropout vs. batch normalization: an empirical study of th... 2020 2026 2022 2024 2020 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Dropout vs. batch normalization: an empirical study of their impact to deep learning
    2020 386 citations Oge Marques et al. Multimedia Tools and Applications profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Oge Marques United States 22 998 632 398 264 224 118 2.3k
Ngai‐Man Cheung Singapore 31 1.9k 1.9× 819 1.3× 146 0.4× 177 0.7× 530 2.4× 142 3.2k
Parvathaneni Naga Srinivasu India 21 385 0.4× 673 1.1× 225 0.6× 274 1.0× 80 0.4× 56 1.8k
Michael A. Riegler Norway 30 1.4k 1.4× 1.4k 2.1× 901 2.3× 1.0k 3.9× 187 0.8× 233 4.4k
Deepika Koundal India 31 748 0.7× 929 1.5× 230 0.6× 582 2.2× 104 0.5× 114 3.2k
Yan Xu China 33 1.6k 1.6× 1.4k 2.3× 228 0.6× 915 3.5× 98 0.4× 242 3.9k
Fayadh Alenezi Saudi Arabia 30 915 0.9× 723 1.1× 171 0.4× 323 1.2× 106 0.5× 123 2.7k
Pål Halvorsen Norway 31 2.2k 2.2× 1.3k 2.0× 902 2.3× 999 3.8× 693 3.1× 313 5.2k
Sheifali Gupta India 24 520 0.5× 596 0.9× 239 0.6× 401 1.5× 50 0.2× 307 2.5k
Paweł Pławiak Poland 31 545 0.5× 1.2k 1.9× 134 0.3× 582 2.2× 258 1.2× 128 4.1k
Soumya Ranjan Nayak India 24 429 0.4× 619 1.0× 124 0.3× 439 1.7× 81 0.4× 123 1.9k

Countries citing papers authored by Oge Marques

Since Specialization
Citations

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

Fields of papers citing papers by Oge Marques

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oge Marques

This figure shows the co-authorship network connecting the top 25 collaborators of Oge Marques. A scholar is included among the top collaborators of Oge Marques 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 Oge Marques. Oge Marques 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
1.
Marques, Oge, et al.. (2024). Overview of the future impact of wearables and artificial intelligence in healthcare workflows and technology. International Journal of Information Management Data Insights. 4(2). 100294–100294. 7 indexed citations
2.
3.
Marques, Oge, et al.. (2023). Diagnostic Efficacy and Clinical Relevance of Artificial Intelligence in Detecting Cognitive Decline. Cureus. 15(10). e47004–e47004. 3 indexed citations
4.
Marques, Oge, et al.. (2023). Skin lesion analysis using generative adversarial networks: a review. Multimedia Tools and Applications. 82(19). 30065–30106. 8 indexed citations
5.
Syed, Tehreem, et al.. (2023). Skin Cancer Classification Using Deep Spiking Neural Network. Journal of Digital Imaging. 36(3). 1137–1147. 65 indexed citations
6.
Marques, Oge, et al.. (2021). Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes. SHILAP Revista de lepidopterología. 8. 2327428260–2327428260. 82 indexed citations
7.
Marques, Oge, et al.. (2021). Image quality issues in teledermatology: A comparative analysis of artificial intelligence solutions. Journal of the American Academy of Dermatology. 87(1). 240–242. 11 indexed citations
8.
Taschwer, Mario, et al.. (2018). Early and Late Fusion of Classifiers for the MediaEval Medico Task.. MediaEval. 2 indexed citations
9.
Marques, Oge, et al.. (2018). ImageCLEF 2018 Tuberculosis Task: Ensemble of 3D CNNs with Multiple Inputs for Tuberculosis Type Classification.. CLEF (Working Notes). 3 indexed citations
10.
Kumar, Pankaj, et al.. (2017). Iris recognition with tunable filter bank based feature. Multimedia Tools and Applications. 77(6). 7637–7674. 28 indexed citations
11.
Marques, Oge, et al.. (2017). Rethinking Skin Lesion Segmentation in a Convolutional Classifier. Journal of Digital Imaging. 31(4). 435–440. 53 indexed citations
12.
Taschwer, Mario & Oge Marques. (2015). AAUITEC at ImageCLEF 2015: Compound Figure Separation.. CLEF (Working Notes). 1 indexed citations
13.
Chatzichristofis, Savvas A., Loukas Bampis, Oge Marques, Mathias Lux, & Yiannis S. Boutalis. (2014). Image Encryption Using the Recursive Attributes of the exclusive-OR Filter.. 9. 125–137. 1 indexed citations
14.
Fonseca, A. M., et al.. (2008). Design and implementation of an optical flow-based autonomous video surveillance system. 209–214. 6 indexed citations
15.
Ćulibrk, Dubravko, Oge Marques, Daniel Socek, Hari Kalva, & Borko Furht. (2007). Neural Network Approach to Background Modeling for Video Object Segmentation. IEEE Transactions on Neural Networks. 18(6). 1614–1627. 124 indexed citations
16.
Socek, Daniel, Spyros S. Magliveras, Dubravko Ćulibrk, et al.. (2007). Digital Video Encryption Algorithms Based on Correlation-Preserving Permutations. 2007. 1–15. 23 indexed citations
17.
Marques, Oge & Borko Furht. (2002). Combining Clustering and Relevance Feedback Techniques in Content-based Image Retrieval.. 86(3-4). 306–311. 1 indexed citations
18.
Marques, Oge & Borko Furht. (1999). Issues in Designing Contemporary Video Database Systems.. 14(4). 43–47. 5 indexed citations
19.
Marques, Oge. (1999). QoS guarantees for multimedia traffic in a wireless environment. CRC Press, Inc. eBooks. 531–548. 1 indexed citations
20.
Marques, Oge, et al.. (1999). How To Design a Virtual Classroom: 10 Easy Steps To Follow.. THE journal. 27(2). 96–98. 14 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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