Andrew D. Bagdanov

7.0k citations
88 papers · 4.0k indexed · 3 hit papers · h-index 26

Andrew D. Bagdanov

84 papers receiving 3.9k citations

Hit Papers

Class-Incremental Learning: Su...3422015202620182022250500750

Peers

Andrew D. Bagdanov
Comparison fields: 5 of 124
  • Computer Vision and Pattern Recognition 3.4k
  • Media Technology 830
  • Artificial Intelligence 1.2k
  • Human-Computer Interaction 94
  • Signal Processing 168
Replace Changick Kim with:
Changick Kim South Korea
Xiaobai Liu United States
Gangshan Wu China
Weiyao Lin China
Feng Zheng China
Wujie Zhou China
Hanzi Wang China
Chu‐Song Chen Taiwan
Frédéric Jurie France
Xia Li China
Andrew D. Bagdanov relative to Changick Kim South Korea Changick Kim's profile →
Citations per field
00.5×2.5×
Changick Kim · 1×
Citations per year

Countries citing papers authored by Andrew D. Bagdanov

Since Specialization
Citations

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

Fields of papers citing papers by Andrew D. Bagdanov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew D. Bagdanov. 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 Andrew D. Bagdanov. The network helps show where Andrew D. Bagdanov may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Andrew D. Bagdanov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andrew D. Bagdanov Line = papers co-authored together Andrew D. Bagdanov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 20242
5 20242
6 202017
7
Class-incremental learning: survey and performance evaluation
202046
8 20194
9 2018203
10 20170
11
Multipage document retrieval by textual and visual representations
201212
12 201149
13
Fusing Global and Local Scale for Semantic Image Segmentation
20114
14 200719
15 2006216
16 20061
17
Style characterization of machine printed texts
20044
18 20035
19 200229
20
Searching in document images: what does the appearance of a document tell us about what it means?
20012

About Andrew D. Bagdanov

Andrew D. Bagdanov is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 88 papers that have together received 4.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (25 papers), Video Surveillance and Tracking Methods (20 papers), Image Retrieval and Classification Techniques (18 papers), Domain Adaptation and Few-Shot Learning (15 papers), Handwritten Text Recognition Techniques (13 papers), Human Pose and Action Recognition (12 papers), Advanced Neural Network Applications (11 papers) and Multimodal Machine Learning Applications (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.4k citations), Media Technology (830 citations) and Artificial Intelligence (1.2k citations). Andrew D. Bagdanov has collaborated with scholars based in Italy, Spain and Netherlands. Frequent co-authors include Joost van de Weijer, Xialei Liu, Alberto Del Bimbo, Iacopo Masi, Dìmosthenis Karatzas, Marc Masana, Anguelos Nicolaou, Antonio M. López, Lluís Gómez and Theo Gevers. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters, International Journal on Document Analysis and Recognition (IJDAR), International Journal of Computer Vision and IEEE Transactions on Image Processing.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026