World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
13563
World Ranking
6338
National Ranking
295

Research.com Recognitions

  • 2013 - IEEE Fellow For contributions to information mining of high resolution synthetic aperature radar and optical earth observation images

Overview

Mihai Datcu is affiliated with the German Aerospace Center in Germany. Their research primarily focuses on engineering and computer science, with significant contributions to aerospace engineering and computer vision and pattern recognition.

The scientist's work spans several subfields, including media technology, artificial intelligence, and oceanography. Their main topics of research cover remote-sensing image classification, advanced SAR imaging techniques, and synthetic aperture radar (SAR) applications and techniques. Additional areas of expertise include advanced image and video retrieval techniques, image retrieval and classification techniques, underwater acoustics research, and sparse and compressive sensing techniques.

Mihai Datcu has co-authored scholarly works with multiple frequent collaborators, including:

  • Andrei Anghel
  • Corneliu Octavian Dumitru
  • Gottfried Schwarz
  • Muhammad Amjad Iqbal
  • Reza Mohammadi Asiyabi

Their recent publications present developments in synthetic aperture radar and explainable artificial intelligence. Some of the notable papers include:

  • "Classification of Large-Scale High-Resolution SAR Images With Deep Transfer Learning" (2020, IEEE Geoscience and Remote Sensing Letters)
  • "Deep SAR-Net: Learning objects from signals" (2020, ISPRS Journal of Photogrammetry and Remote Sensing)
  • "Physically explainable CNN for SAR image classification" (2022, ISPRS Journal of Photogrammetry and Remote Sensing)
  • "CMIR-NET: A deep learning based model for cross-modal retrieval in remote sensing" (2020, Pattern Recognition Letters)
  • "Explainable, Physics-Aware, Trustworthy Artificial Intelligence: A paradigm shift for synthetic aperture radar" (2023, IEEE Geoscience and Remote Sensing Magazine)

The venues where Mihai Datcu has frequently published include:

  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • arXiv (Cornell University)
  • IEEE Geoscience and Remote Sensing Letters
  • IEEE Transactions on Geoscience and Remote Sensing

In recognition of their contributions, Mihai Datcu was named an IEEE Fellow in 2013 for work related to information mining of high-resolution synthetic aperture radar and optical earth observation images.

Best Publications

  • DOTA: A Large-Scale Dataset for Object Detection in Aerial Images

    Gui-Song Xia;Xiang Bai;Jian Ding;Zhen Zhu

  • Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks

    Dimitrios Marmanis;Mihai Datcu;Thomas Esch;Uwe Stilla

  • Classification With an Edge: Improving Semantic Image Segmentation with Boundary Detection

    Dimitrios Marmanis;Dimitrios Marmanis;Konrad Schindler;Jan Dirk Wegner;Silvano Galliani

  • Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges

    Jian Ding;Nan Xue;Gui-Song Xia;Xiang Bai

  • SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS

    Dimitrios Marmanis;Dimitrios Marmanis;Jan D. Wegner;Silvano Galliani;Konrad Schindler

  • Information mining in remote sensing image archives: system concepts

    M. Datcu;H. Daschiel;A. Pelizzari;M. Quartulli

  • Semantic Annotation of Satellite Images Using Latent Dirichlet Allocation

    M. Lienou;H. Maitre;M. Datcu

  • Model-based despeckling and information extraction from SAR images

    Marc Walessa;Mihai Datcu

  • Spatial information retrieval from remote-sensing images. I. Information theoretical perspective

    M. Datcu;K. Seidel;M. Walessa

  • Interactive learning and probabilistic retrieval in remote sensing image archives

    M. Schroder;H. Rehrauer;K. Seidel;M. Datcu

  • Spatial information retrieval from remote-sensing images. II. Gibbs-Markov random fields

    M. Schroder;H. Rehrauer;K. Seidel;M. Datcu

  • Road detection in dense urban areas using SAR imagery and the usefulness of multiple views

    F. Tupin;B. Houshmand;M. Datcu

  • Bayesian approaches to phase unwrapping: theoretical study

    G. Nico;G. Palubinskas;M. Datcu

  • Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

    Xin-Yi Tong;Gui-Song Xia;Fan Hu;Yanfei Zhong

  • Stochastic geometrical modeling for built-up area understanding from a single SAR intensity image with meter resolution

    M. Quartulli;M. Datcu

  • Human-centered concepts for exploration and understanding of Earth observation images

    M. Datcu;K. Seidel

  • Classification of Large-Scale High-Resolution SAR Images With Deep Transfer Learning

    Zhongling Huang;Corneliu Octavian Dumitru;Zongxu Pan;Bin Lei

  • Deep SAR-Net: Learning objects from signals

    Zhongling Huang;Mihai Datcu;Zongxu Pan;Bin Lei

  • Bridging the Semantic Gap for Satellite Image Annotation and Automatic Mapping Applications

    D Bratasanu;I Nedelcu;M Datcu

  • Earth-Observation Image Retrieval Based on Content, Semantics, and Metadata

    Daniela Espinoza-Molina;Mihai Datcu

  • Information Content of Very High Resolution SAR Images: Study of Feature Extraction and Imaging Parameters

    Corneliu Octavian Dumitru;Mihai Datcu

Frequent Co-Authors

Gerhard Rigoll
Gerhard Rigoll Technical University of Munich
Gui-Song Xia
Gui-Song Xia Wuhan University
Liangpei Zhang
Liangpei Zhang Wuhan University
Manolis Koubarakis
Manolis Koubarakis National and Kapodistrian University of Athens
Xiang Bai
Xiang Bai Huazhong University of Science and Technology
Marcello Pelillo
Marcello Pelillo Ca Foscari University of Venice
Uwe Stilla
Uwe Stilla Technical University of Munich
Jiebo Luo
Jiebo Luo University of Rochester
Serge Belongie
Serge Belongie University of Copenhagen

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