Óscar Déniz

7.6k citations
112 papers · 2.4k indexed · 1 hit paper · h-index 23

Óscar Déniz

102 papers receiving 2.3k citations

Hit Papers

Face recognition using Histograms of Oriented Gradients4212011202620162021100200300400

Peers

Óscar Déniz
Comparison fields: 5 of 166
  • Computer Vision and Pattern Recognition 1.4k
  • Biophysics 194
  • Artificial Intelligence 891
  • Media Technology 218
  • Signal Processing 231
Replace Gloria Bueno with:
Gloria Bueno Spain
Stella X. Yu United States
Costantino Grana Italy
Alexander A. Alemi United States
Sim Heng Ong Singapore
Takio Kurita Japan
Jianbo Shi United States
Filiz Bunyak United States
Hélio Pedrini Brazil
Saad Albawi Iraq
Óscar Déniz relative to Gloria Bueno Spain Gloria Bueno's profile →
Citations per field
00.5×1.5×1.8×
Gloria Bueno · 1×
Citations per year

Countries citing papers authored by Óscar Déniz

Since Specialization
Citations

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

Fields of papers citing papers by Óscar Déniz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Óscar Déniz, 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 Óscar Déniz Line = papers co-authored together Óscar Déniz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202346
3 202313
4 20233
5 202214
6 202137
7 202126
8 20204
9 202018
10 201813
11 201716
12 201642
13 20151
14
A CAD System for the Acquisition and Classification of Breast TMA in Pathology.
20156
15
Fast violence detection in video
20151
16
VISILAB at MediaEval 2013: Fight Detection.
20135
17 201312
18
Security System Based on Suspicious Behavior Detection
20102
19 20099
20
BDIE: a BDI like architecture with emotional capabilities
20046

About Óscar Déniz

Óscar Déniz is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Artificial Intelligence, having authored 112 papers that have together received 2.4k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (24 papers), AI in cancer detection (24 papers), Face and Expression Recognition (14 papers), Video Surveillance and Tracking Methods (13 papers), Adversarial Robustness in Machine Learning (12 papers), Face recognition and analysis (11 papers), Cell Image Analysis Techniques (11 papers) and Image Processing Techniques and Applications (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Biophysics (194 citations) and Artificial Intelligence (891 citations). Óscar Déniz has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Gloria Bueno, Jesús Salido, Modesto Castrillón-Santana, Fernando De la Torre, M. Hernández, Noelia Vállez, M. Milagro Fernández-Carrobles, Gabriel Cristóbal, Ismael Serrano and Jesús Ruiz-Santaquiteria. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE 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.

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