2011 - Member of Academia Europaea
His primary scientific interests are in Artificial intelligence, Computer vision, Algorithm, Image processing and Mathematical analysis. His biological study spans a wide range of topics, including Mathematical economics, Geodesic and Pattern recognition. His studies deal with areas such as Smoothing, Flow, Mathematical optimization, Nonlinear system and Optical flow as well as Algorithm.
His Optical flow study combines topics from a wide range of disciplines, such as Energy functional, Image warping, Motion estimation, Multigrid method and Robustness. His Image processing research is multidisciplinary, relying on both Anisotropic diffusion, Structure tensor, Filter and Coherence. His work carried out in the field of Mathematical analysis brings together such families of science as Regularization, Noise reduction, Total variation denoising and Applied mathematics.
Joachim Weickert spends much of his time researching Artificial intelligence, Algorithm, Computer vision, Mathematical analysis and Image processing. His study ties his expertise on Pattern recognition together with the subject of Artificial intelligence. His research investigates the connection between Algorithm and topics such as Anisotropic diffusion that intersect with issues in Isotropy.
His research in Mathematical analysis intersects with topics in Shrinkage, Haar wavelet, Wavelet and Scale space. In his study, which falls under the umbrella issue of Image processing, Tensor field is strongly linked to Structure tensor. His Partial differential equation research incorporates themes from Numerical analysis, Mathematical optimization, Applied mathematics and Dilation.
Inpainting, Algorithm, Artificial intelligence, Computer vision and Applied mathematics are his primary areas of study. His study in Inpainting is interdisciplinary in nature, drawing from both Anisotropic diffusion, Data compression, Image compression and Compression. Joachim Weickert combines subjects such as Margin, Noise reduction and Filter with his study of Algorithm.
His research brings together the fields of Pattern recognition and Artificial intelligence. His work deals with themes such as Sequence and Interpolation, which intersect with Computer vision. His Applied mathematics study incorporates themes from Gradient descent, Regularization and Uniqueness, Mathematical analysis.
His scientific interests lie mostly in Inpainting, Artificial intelligence, Computer vision, Partial differential equation and Algorithm. Joachim Weickert interconnects Anisotropic diffusion, Probabilistic logic, Image compression and Applied mathematics in the investigation of issues within Inpainting. His study looks at the relationship between Anisotropic diffusion and topics such as Convex function, which overlap with Image processing.
His research on Artificial intelligence often connects related topics like Pattern recognition. Joachim Weickert integrates many fields, such as Algorithm and Orders of magnitude, in his works. The Mathematical analysis study combines topics in areas such as Transformation and Scale space.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Anisotropic diffusion in image processing
High Accuracy Optical Flow Estimation Based on a Theory for Warping
Thomas Brox;Andr ´ es Bruhn;Nils Papenberg;Joachim Weickert.
european conference on computer vision (2004)
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
Andrés Bruhn;Joachim Weickert;Christoph Schnörr.
International Journal of Computer Vision (2005)
Efficient and reliable schemes for nonlinear diffusion filtering
J. Weickert;B.M.T.H. Romeny;M.A. Viergever.
IEEE Transactions on Image Processing (1998)
Coherence-Enhancing Diffusion Filtering
International Journal of Computer Vision (1999)
A Review of Nonlinear Diffusion Filtering
Lecture Notes in Computer Science (1997)
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
Nils Papenberg;Andrés Bruhn;Thomas Brox;Stephan Didas.
International Journal of Computer Vision (2006)
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
Daniel Cremers;Florian Tischhäuser;Joachim Weickert;Christoph Schnörr.
International Journal of Computer Vision (2002)
Reliable Estimation of Dense Optical Flow Fields with Large Displacements
Luis Alvarez;Joachim Weickert;Javier Sánchez.
International Journal of Computer Vision (2000)
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
Joachim Weickert;Christoph Schnörr.
International Journal of Computer Vision (2001)
Profile was last updated on December 6th, 2021.
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