Dan Pescaru

413 citations
44 papers · 260 · h-index 9

Impact in

Papers in

Dan Pescaru

38 papers receiving 242 citations

Peers

Dan Pescaru
Comparison fields: 5 of 63
  • Computer Networks and Communications 105
  • Computer Vision and Pattern Recognition 79
  • Software 13
  • Hardware and Architecture 18
  • Artificial Intelligence 61
Replace Siegfried Mercelis with:
Siegfried Mercelis Belgium
Kalinka Regina Lucas Jaquie Castelo Branco Brazil
Hamra Afzaal Pakistan
Haitao Zhang China
Kai Cheng China
Tiehua Zhang Australia
Péter Ekler Hungary
Matthias Woehrle Switzerland
Wubin Li Canada
Dan Pescaru relative to Siegfried Mercelis Belgium Siegfried Mercelis's profile →
Citations per field
00.5×1.5×2.3×
Siegfried Mercelis · 1×
Citations per year

Countries citing papers authored by Dan Pescaru

Since Specialization
Citations

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

Fields of papers citing papers by Dan Pescaru

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Dan Pescaru, 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 Dan Pescaru Line = papers co-authored together Dan Pescaru links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201941
2
Redundancy and its applications in wireless sensor networks: a survey
200926
3 200525
4 201424
5 200812
6 200711
7 201011
8 200810
9 20238
10 20138
11 20086
12 20116
13 20146
14 20165
15 20085
16 20105
17
A view upon redundancy in wireless sensor networks
20094
18 20124
19 20124
20 20104

About Dan Pescaru

Dan Pescaru is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering and Hardware and Architecture, having authored 44 papers that have together received 260 indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (16 papers), Video Surveillance and Tracking Methods (9 papers), Embedded Systems Design Techniques (7 papers), Real-Time Systems Scheduling (6 papers), Mobile Ad Hoc Networks (5 papers), Underwater Vehicles and Communication Systems (4 papers), Advanced Software Engineering Methodologies (4 papers) and Indoor and Outdoor Localization Technologies (4 papers). The work is most often cited by research in Computer Networks and Communications (105 citations), Computer Vision and Pattern Recognition (79 citations), Software (13 citations), Hardware and Architecture (18 citations) and Artificial Intelligence (61 citations). Dan Pescaru has collaborated with scholars based in Romania, United States and France. Frequent co-authors include Daniel-Ioan Curiac, Alex Doboli, Constantin Voloşencu, Alexa Doboli, Mihai V. Micea, Dan Cireşan, Meng Wang, Bogdan Ciubotaru, Yang Zhao and Vladimir Creţu. Their work appears in journals such as Sensors, ACM Transactions on Embedded Computing Systems, IEEE Transactions on Intelligent Transportation Systems, Transportation Research Part C Emerging Technologies and International Conference on Signal 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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