What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Computer vision
Dirk Vandermeulen mainly focuses on Artificial intelligence, Computer vision, Image registration, Segmentation and Pattern recognition.
In his research, Dirk Vandermeulen undertakes multidisciplinary study on Artificial intelligence and Visual Word.
His work focuses on many connections between Computer vision and other disciplines, such as Magnetic resonance imaging, that overlap with his field of interest in Contextual image classification.
His Image registration research incorporates themes from Multi modality, Medical imaging, Matching, Mutual information and Information theory.
His work deals with themes such as Outlier and Atlas, which intersect with Segmentation.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Feature and Statistical model.
His most cited work include:
- Multimodality image registration by maximization of mutual information (3987 citations)
- Automated model-based tissue classification of MR images of the brain (928 citations)
- Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques (827 citations)
What are the main themes of his work throughout his whole career to date?
Dirk Vandermeulen mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Image registration.
His work in Mutual information, Image segmentation, Voxel, Facial recognition system and Landmark is related to Artificial intelligence.
His Computer vision study incorporates themes from Medical imaging, Outlier, Mr images, Visualization and Robustness.
His Pattern recognition research includes themes of Dice, Histogram, Face and Feature.
His Segmentation research integrates issues from Brain atlas, Ground truth, Image and Atlas.
Dirk Vandermeulen combines topics linked to Similarity measure with his work on Image registration.
He most often published in these fields:
- Artificial intelligence (66.41%)
- Computer vision (42.97%)
- Pattern recognition (31.25%)
What were the highlights of his more recent work (between 2011-2021)?
- Artificial intelligence (66.41%)
- Pattern recognition (31.25%)
- Segmentation (22.40%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Segmentation, Computer vision and Convolutional neural network.
His Deep learning, Image segmentation, Face, Landmark and Representation investigations are all subjects of Artificial intelligence research.
The study incorporates disciplines such as Facial recognition system, Similarity, Dice and Facial morphology in addition to Pattern recognition.
His studies in Segmentation integrate themes in fields like Voxel and Feature.
All of his Computer vision and Shape analysis and Image registration investigations are sub-components of the entire Computer vision study.
His Convolutional neural network study combines topics from a wide range of disciplines, such as Molar, Radiology and Osteoporosis.
Between 2011 and 2021, his most popular works were:
- Modeling 3D facial shape from DNA (171 citations)
- A comparison of methods for non-rigid 3D shape retrieval (137 citations)
- meshSIFT: Local surface features for 3D face recognition under expression variations and partial data (106 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Computer vision
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Evolutionary biology and Image segmentation.
His studies deal with areas such as Panoramic radiograph and Cohen's kappa as well as Artificial intelligence.
His Pattern recognition research includes elements of Facial recognition system, Face, Software and Deep learning.
In his works, Dirk Vandermeulen performs multidisciplinary study on Computer vision and Antihelix.
His work carried out in the field of Segmentation brings together such families of science as Image registration, Maximization and Cluster analysis.
The various areas that he examines in his Image registration study include Visualization, Voxel, Multimodality and Mutual information.
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