What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Segmentation, Pattern recognition and Image registration.
His Artificial intelligence research includes themes of Machine learning and Geodesic.
His Segmentation study integrates concerns from other disciplines, such as Object and Brain tumor.
His Pattern recognition study incorporates themes from Contextual image classification, Curse of dimensionality and Sensor fusion.
His Image registration research integrates issues from Embedding, Markov random field, Linear programming, Mathematical optimization and Discrete optimization.
Nikos Paragios studied Image segmentation and Medical imaging that intersect with Tracking.
His most cited work include:
- Geodesic active contours and level sets for the detection and tracking of moving objects (927 citations)
- Deformable Medical Image Registration: A Survey (926 citations)
- Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation (718 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Image segmentation.
The concepts of his Artificial intelligence study are interwoven with issues in Algorithm and Machine learning.
His Computer vision research is multidisciplinary, incorporating elements of Graphical model, Discrete optimization and Graph.
His Active shape model study, which is part of a larger body of work in Pattern recognition, is frequently linked to Prior probability, bridging the gap between disciplines.
His work on Active contour model as part of general Segmentation study is frequently linked to Gesture recognition, therefore connecting diverse disciplines of science.
His biological study spans a wide range of topics, including Similarity and Medical imaging.
He most often published in these fields:
- Artificial intelligence (83.29%)
- Computer vision (47.04%)
- Pattern recognition (34.19%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (83.29%)
- Deep learning (7.71%)
- Pattern recognition (34.19%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Deep learning, Pattern recognition, Machine learning and Segmentation.
His works in Convolutional neural network, Image registration, Similarity, Artificial neural network and Medical imaging are all subjects of inquiry into Artificial intelligence.
Similarity is a subfield of Computer vision that Nikos Paragios studies.
He integrates many fields, such as Computer vision and Displacement, in his works.
His Pattern recognition research includes elements of Function and Protein structure.
His work on Image segmentation and Tumor segmentation as part of general Segmentation research is frequently linked to Code, bridging the gap between disciplines.
Between 2016 and 2021, his most popular works were:
- Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (493 citations)
- A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study (297 citations)
- A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study (297 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His main research concerns Artificial intelligence, Deep learning, Pattern recognition, Medical imaging and Machine learning.
The various areas that Nikos Paragios examines in his Artificial intelligence study include Protein structure, Algorithm and Magnetic resonance imaging.
His research in Deep learning intersects with topics in Similarity, Outcome prediction, Intensive care, Image registration and Convolutional neural network.
His study in the fields of Feature selection under the domain of Pattern recognition overlaps with other disciplines such as Standardization.
His Medical imaging research incorporates themes from Perspective and Medical physics.
Nikos Paragios is interested in Scale-space segmentation, which is a branch of Computer vision.
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.
