Svebor Karaman

1.5k total citations
21 papers, 357 citations indexed

About

Svebor Karaman is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Svebor Karaman has authored 21 papers receiving a total of 357 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 3 papers in Biomedical Engineering. Recurrent topics in Svebor Karaman's work include Video Surveillance and Tracking Methods (8 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Human Pose and Action Recognition (5 papers). Svebor Karaman is often cited by papers focused on Video Surveillance and Tracking Methods (8 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Human Pose and Action Recognition (5 papers). Svebor Karaman collaborates with scholars based in United States, Italy and Spain. Svebor Karaman's co-authors include Shih‐Fu Chang, Felix X. Yu, Alberto Del Bimbo, Giuseppe Lisanti, Xu Zhang, Shih-Fu Chang, Andrew D. Bagdanov, Alireza Zareian, Iacopo Masi and Lorenzo Seidenari and has published in prestigious journals such as Pattern Recognition, Alzheimer s & Dementia and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Svebor Karaman

21 papers receiving 343 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Svebor Karaman United States 11 282 110 54 33 20 21 357
Marwa Elpeltagy Egypt 8 149 0.5× 109 1.0× 48 0.9× 34 1.0× 31 1.6× 9 317
Peipei Yang China 9 122 0.4× 129 1.2× 16 0.3× 15 0.5× 9 0.5× 28 243
Andrei Barbu United States 9 267 0.9× 263 2.4× 13 0.2× 27 0.8× 9 0.5× 22 376
Marco Hutter Switzerland 8 126 0.4× 85 0.8× 27 0.5× 62 1.9× 8 0.4× 24 263
Amir Tamrakar United States 9 254 0.9× 105 1.0× 14 0.3× 11 0.3× 10 0.5× 22 343
Yan Ke United States 7 435 1.5× 122 1.1× 32 0.6× 52 1.6× 27 1.4× 9 467
Hyung–Il Choi South Korea 8 176 0.6× 47 0.4× 29 0.5× 16 0.5× 19 0.9× 37 224
Zhangzhang Si United States 9 348 1.2× 149 1.4× 31 0.6× 10 0.3× 8 0.4× 15 416
Hyun-Ki Hong South Korea 10 158 0.6× 18 0.2× 71 1.3× 16 0.5× 20 1.0× 58 254

Countries citing papers authored by Svebor Karaman

Since Specialization
Citations

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

Fields of papers citing papers by Svebor Karaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Svebor Karaman

This figure shows the co-authorship network connecting the top 25 collaborators of Svebor Karaman. A scholar is included among the top collaborators of Svebor Karaman 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 Svebor Karaman. Svebor Karaman 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.
Zhang, Xu, Zhaohui Sun, Svebor Karaman, & Shih-Fu Chang. (2020). Discovering Image Manipulation History by Pairwise Relation and Forensics Tools. IEEE Journal of Selected Topics in Signal Processing. 14(5). 1012–1023. 14 indexed citations
2.
Patton, Desmond U., et al.. (2019). Multimodal Social Media Analysis for Gang Violence Prevention. Proceedings of the International AAAI Conference on Web and Social Media. 13. 114–124. 13 indexed citations
3.
Patton, Desmond U., et al.. (2019). Annotating Social Media Data From Vulnerable Populations: Evaluating Disagreement Between Domain Experts and Graduate Student Annotators. Proceedings of the ... Annual Hawaii International Conference on System Sciences. 9 indexed citations
4.
Akbari, Hassan, et al.. (2019). Multi-Level Multimodal Common Semantic Space for Image-Phrase Grounding. 12468–12478. 38 indexed citations
5.
Karaman, Svebor, et al.. (2019). Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval. 192–196. 9 indexed citations
6.
Lisanti, Giuseppe, et al.. (2018). Scene-dependent proposals for efficient person detection. Pattern Recognition. 87. 170–178. 4 indexed citations
7.
Lisanti, Giuseppe, Svebor Karaman, & Iacopo Masi. (2017). Multichannel-Kernel Canonical Correlation Analysis for Cross-View Person Reidentification. ACM Transactions on Multimedia Computing Communications and Applications. 13(2). 1–19. 35 indexed citations
8.
Zhang, Xu, Felix X. Yu, Svebor Karaman, & Shih‐Fu Chang. (2017). Learning Discriminative and Transformation Covariant Local Feature Detectors. 4923–4931. 84 indexed citations
9.
Karaman, Svebor, et al.. (2016). Placing Broadcast News Videos in their Social Media Context Using Hashtags. 684–688. 1 indexed citations
10.
Seidenari, Lorenzo, et al.. (2015). Efficient hough forest object detection for low-power devices. Florence Research (University of Florence). 3. 1–6. 2 indexed citations
11.
Lisanti, Giuseppe, et al.. (2015). MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 19–27. 10 indexed citations
12.
Seidenari, Lorenzo, et al.. (2015). WATTS. 701–704. 2 indexed citations
13.
Karaman, Svebor, et al.. (2015). MORF: Multi-Objective Random Forests for face characteristic estimation. Florence Research (University of Florence). 1–6. 4 indexed citations
14.
Karaman, Svebor, Lorenzo Seidenari, Shugao Ma, Alberto Del Bimbo, & Stan Sclaroff. (2014). Adaptive Structured Pooling for Action Recognition. 112.1–112.12. 7 indexed citations
15.
Lisanti, Giuseppe, et al.. (2014). Unsupervised Scene Adaptation for Faster Multi-scale Pedestrian Detection. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 3534–3539. 5 indexed citations
16.
Karaman, Svebor, Giuseppe Lisanti, Andrew D. Bagdanov, & Alberto Del Bimbo. (2014). Leveraging local neighborhood topology for large scale person re-identification. Pattern Recognition. 47(12). 3767–3778. 19 indexed citations
17.
Karaman, Svebor, et al.. (2014). Personalized multimedia content delivery on an interactive table by passive observation of museum visitors. Multimedia Tools and Applications. 75(7). 3787–3811. 34 indexed citations
18.
Karaman, Svebor, Lorenzo Seidenari, Andrew D. Bagdanov, & Alberto Del Bimbo. (2013). L1-regularized Logistic Regression Stacking and Transductive CRF Smoothing for Action Recognition in Video. 15 indexed citations
19.
Karaman, Svebor, et al.. (2011). P1‐413: Autonomy at home and early diagnosis in AD: Utility of video indexing applied to clinical issues, the IMMED project. Alzheimer s & Dementia. 7(4S_Part_7). 2 indexed citations
20.
Mégret, Rémi, Hazem Wannous, Svebor Karaman, et al.. (2010). The IMMED project. 1299–1302. 15 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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