Dinu Coltuc

Computer Vision and Pattern Recognition · 2006–2014

A researcher in the Science corpus: 4 papers; trusts 31 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Dinu Coltuc trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Jun Tian
  2. Diljith M. Thodi
  3. Mehmet Utku Celik
  4. Marcelo J. Weinberger
  5. Wien Hong
  6. Jessica J. Fridrich
  7. Jeffrey J. Rodríguez
  8. Vasiliy Sachnev
  9. Gadiel Seroussi
  10. Gaurav Sharma

Who trusts Dinu Coltuc overall

  1. Xiaolong Li
  2. Y. Shi
  3. Ioan-Catalin Dragoi
  4. Massimo Salvi
  5. Xueyang Fu
  6. Wenqi Ren
  7. Weiming Zhang
  8. Bin Yang
  9. Xinpeng Zhang
  10. Hao-Tian Wu

Papers from Dinu Coltuc's perspective

Ordered by how strongly the researchers Dinu Coltuc trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Circular interpretation of bijective transformations in lossless watermarking for media asset management (IEEE Trans. Multim.)
  2. Lossless generalized-LSB data embedding (IEEE Transactions on Image Processing)
  3. Reversible data embedding using a difference expansion (IEEE Trans. Circuits Syst. Video Technol.)
  4. Reversible data hiding (Proceedings. International Conference on Image Processing)
  5. Reversible data embedding into images using wavelet techniques and sorting (IEEE Transactions on Image Processing)
  6. Lossless Data Embedding—New Paradigm in Digital Watermarking (EURASIP Journal on Advances in Signal Processing)
  7. Expansion Embedding Techniques for Reversible Watermarking (IEEE Transactions on Image Processing)
  8. Invertible authentication (Security and Watermarking of Multimedia Contents)
  9. Reversible Image Watermarking Based on Integer-to-Integer Wavelet Transform (IEEE Transactions on Information Forensics and Security)
  10. The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS (IEEE Transactions on Image Processing)

Their papers