What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Mathematical analysis
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.
His most cited work include:
- High Accuracy Optical Flow Estimation Based on a Theory for Warping (2068 citations)
- Anisotropic diffusion in image processing (1728 citations)
- Efficient and reliable schemes for nonlinear diffusion filtering (985 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (36.02%)
- Algorithm (31.74%)
- Computer vision (30.73%)
What were the highlights of his more recent work (between 2015-2021)?
- Inpainting (11.59%)
- Algorithm (31.74%)
- Artificial intelligence (36.02%)
In recent papers he was focusing on the following fields of study:
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.
Between 2015 and 2021, his most popular works were:
- Fast retinal vessel analysis (38 citations)
- Cyclic Schemes for PDE-Based Image Analysis (37 citations)
- Turning Diffusion-Based Image Colorization Into Efficient Color Compression (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mathematical analysis
- Computer vision
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.
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