Moises Díaz

3.6k citations
87 papers · 2.4k indexed · 1 hit paper · h-index 23

Impact in

Papers in

Moises Díaz

75 papers receiving 2.3k citations

Hit Papers

Apoptotic Cells Promote Their Own Clearance and Immune Tolerance through Activation of the Nuclear Receptor LXR 2009 · 544 citations
5442009202620142020100200300400500

Peers

Moises Díaz
Comparison fields: 5 of 141
  • Computer Vision and Pattern Recognition 1.1k
  • Media Technology 345
  • Human-Computer Interaction 208
  • Immunology 606
  • Signal Processing 191
Replace Narendra D. Londhe with:
Narendra D. Londhe India
Wei‐Yen Hsu Taiwan
Shunji Mori Japan
Kenji Hata Japan
Markus Reischl Germany
Sudipta Roy India
Martti Juhola Finland
Chen Qian China
Malay Kishore Dutta India
Di Xie China
Moises Díaz relative to Narendra D. Londhe India Narendra D. Londhe's profile →
Citations per field
00.5×8.4×
Narendra D. Londhe · 1×
Citations per year

Countries citing papers authored by Moises Díaz

Since Specialization
Citations

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

Fields of papers citing papers by Moises Díaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Apoptotic Cells Promote Their Own Clearance and Immune Tolerance through Activation of the Nuclear Receptor LXR
Hit paper breakdown →
2009544
2 2019144
3 2013142
4 201696
5 201694
6 201591
7 201487
8 201285
9 201483
10 202072
11 201971
12 202069
13 201259
14 201659
15 201357
16 201547
17 201643
18 201541
19 201838
20 201835

About Moises Díaz

Moises Díaz is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence, Signal Processing and Media Technology, having authored 87 papers that have together received 2.4k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (50 papers), Image Processing and 3D Reconstruction (21 papers), Natural Language Processing Techniques (20 papers), Hand Gesture Recognition Systems (14 papers), Image Retrieval and Classification Techniques (9 papers), Biometric Identification and Security (5 papers), Vehicle License Plate Recognition (5 papers) and Robot Manipulation and Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Media Technology (345 citations), Human-Computer Interaction (208 citations), Immunology (606 citations) and Signal Processing (191 citations). Moises Díaz has collaborated with scholars based in Spain, Italy and Canada. Frequent co-authors include Miguel A. Ferrer, Aythami Morales, Réjean Plamondon, Donato Impedovo, Giuseppe Pirlo, Antonio Castrillo, Pietro Cerri, Cynthia Hong, Peter Tontonoz and Andreas Fischer. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters, Cognitive Computation, Expert Systems with Applications and Pattern Recognition.

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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