Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
DOTA: A Large-Scale Dataset for Object Detection in Aerial Images
20182.1k citationsGui-Song Xia, Xiang Bai et al.elib (German Aerospace Center)profile →
Classification with an edge: Improving semantic image segmentation
\nwith boundary detection
2018505 citationsKonrad Schindler, Mihai Datcu et al.profile →
Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks
2015488 citationsMihai Datcu et al.IEEE Geoscience and Remote Sensing Lettersprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Mihai Datcu'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 Mihai Datcu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mihai Datcu more than expected).
This network shows the impact of papers produced by Mihai Datcu. 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 Mihai Datcu. The network helps show where Mihai Datcu may publish in the future.
Co-authorship network of co-authors of Mihai Datcu
This figure shows the co-authorship network connecting the top 25 collaborators of Mihai Datcu.
A scholar is included among the top collaborators of Mihai Datcu based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Mihai Datcu. Mihai Datcu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Clerc, Sébastien, et al.. (2016). New perspectives for the observation of coastal zones with the Coastal Thematic Exploitation Platform. elib (German Aerospace Center). 740. 27.1 indexed citations
15.
Neagoe, Victor-Emil, et al.. (2011). A neural network approach for land-cover change detection in multi-temporal multispectral remote-sensing imagery. International Conference on Signal Processing. 221–226.4 indexed citations
16.
Datcu, Mihai, et al.. (2010). Support for Automation of Cartography Based on Earth Observation Images- A Data Mining Approach. 686. 476.
17.
Datcu, Mihai, et al.. (2010). Assessment of two Gibbs random field based feature extraction methods for SAR images using a Cramer-Rao bound. 1–4.1 indexed citations
Datcu, Mihai, et al.. (2002). Knowledge-driven Information-Mining in Remote Sensing Image Archives. elib (German Aerospace Center). 110(110). 26–33.23 indexed citations
20.
Seidel, K. & Mihai Datcu. (1993). Fusion of Real and Synthetic Images for Remote Sensing Scene Understanding. elib (German Aerospace Center).4 indexed citations
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.