Daniel Keren

1.3k citations
56 papers · 827 indexed · h-index 18

Daniel Keren

52 papers receiving 797 citations

Peers

Daniel Keren
Comparison fields: 5 of 94
  • Signal Processing 197
  • Computer Networks and Communications 366
  • Computer Graphics and Computer-Aided Design 41
  • Computer Vision and Pattern Recognition 210
  • Artificial Intelligence 271
Replace Geng Zhao with:
Geng Zhao China
Jizhong Han China
Lixin Han China
Bo Wu United States
Lawrence D. Bergman United States
Tae‐Sun Chung South Korea
Emmanuel Pietriga France
H. Vicky Zhao China
Chenglong Wang China
Toshinori Munakata United States
Daniel Keren relative to Geng Zhao China Geng Zhao's profile →
Citations per field
00.5×1.5×2.4×
Geng Zhao · 1×
Citations per year

Countries citing papers authored by Daniel Keren

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Keren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20230
2 20220
3 20175
4
K-hyperplane Hinge-Minimax Classifier
20154
5
Latent Fault Detection With Unbalanced Workloads
20155
6 201514
7 20157
8 20147
9
Communication-efficient Outlier Detection for Scale-out Systems.
20133
10 201334
11 201135
12 20104
13 20100
14 20080
15 20085
16 200761
17 200687
18 200642
19 200317
20 199815

About Daniel Keren

Daniel Keren is a scholar working on Signal Processing, Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence and Transportation, having authored 56 papers that have together received 827 indexed citations. Recurring topics across this work include Data Management and Algorithms (12 papers), Data Stream Mining Techniques (12 papers), Advanced Database Systems and Queries (10 papers), Advanced Vision and Imaging (7 papers), Robotics and Sensor-Based Localization (6 papers), Transportation and Mobility Innovations (5 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Image and Object Detection Techniques (4 papers). The work is most often cited by research in Signal Processing (197 citations), Computer Networks and Communications (366 citations), Computer Graphics and Computer-Aided Design (41 citations), Computer Vision and Pattern Recognition (210 citations) and Artificial Intelligence (271 citations). Daniel Keren has collaborated with scholars based in Israel, United States and Belgium. Frequent co-authors include Assaf Schuster, Izchak Sharfman, Margarita Osadchy, Vasilis Samoladas, Minos Garofalakis, Ehud Rivlin, Moshe Gabel, Irad Yavneh, Evgeni Magid and Hagit Hel‐Or. Their work appears in journals such as Proceedings of the VLDB Endowment, Journal of Mathematical Imaging and Vision, Journal of Parallel and Distributed Computing, IEEE Transactions on Pattern Analysis and Machine Intelligence and Sensors.

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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