H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 39 Citations 33,553 90 World Ranking 4793 National Ranking 212

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Geometry

His primary areas of investigation include Cut, Artificial intelligence, Graph cuts in computer vision, Algorithm and Image segmentation. He performs multidisciplinary study in the fields of Cut and Energy minimization via his papers. Yuri Boykov combines subjects such as Graph theory and Computer vision with his study of Artificial intelligence.

His Graph cuts in computer vision research is multidisciplinary, incorporating perspectives in Hypersurface, Maximum flow problem and Discrete mathematics. His study in Algorithm is interdisciplinary in nature, drawing from both Randomized algorithms as zero-sum games and Graph. His Minimum cut research focuses on subjects like Computational complexity theory, which are linked to Simulated annealing, Standard algorithms, Approximation algorithm and Probabilistic analysis of algorithms.

His most cited work include:

  • Fast approximate energy minimization via graph cuts (6224 citations)
  • An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision (4041 citations)
  • Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images (3422 citations)

What are the main themes of his work throughout his whole career to date?

Yuri Boykov spends much of his time researching Artificial intelligence, Segmentation, Algorithm, Cut and Image segmentation. His Artificial intelligence research is multidisciplinary, incorporating elements of Computer vision and Pattern recognition. His work carried out in the field of Segmentation brings together such families of science as Object, Normalization, Deep learning and Prior probability.

His Algorithm study integrates concerns from other disciplines, such as Vector field, Cluster analysis and Markov model. Yuri Boykov works on Cut which deals in particular with Graph cuts in computer vision. In his research, Pairwise comparison and Maxima and minima is intimately related to Mathematical optimization, which falls under the overarching field of Image segmentation.

He most often published in these fields:

  • Artificial intelligence (58.59%)
  • Segmentation (38.28%)
  • Algorithm (36.72%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (58.59%)
  • Segmentation (38.28%)
  • Algorithm (36.72%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Segmentation, Algorithm, Deep learning and Pattern recognition. Artificial intelligence is represented through his Artificial neural network, Leverage, Entropy, Normalization and Kernel research. Yuri Boykov studies Segmentation, namely Image segmentation.

The study incorporates disciplines such as Augmented reality, Machine learning and Image compression in addition to Image segmentation. His research integrates issues of Geodesic and Pairwise comparison in his study of Algorithm. His work deals with themes such as Vector field, Curvature, Spectral clustering and Kernel clustering, which intersect with Regularization.

Between 2018 and 2021, his most popular works were:

  • Image Segmentation Using Deep Learning: A Survey (107 citations)
  • Constrained-CNN losses for weakly supervised segmentation. (85 citations)
  • Image Segmentation Using Deep Learning: A Survey. (34 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Geometry
  • Machine learning

His main research concerns Image segmentation, Segmentation, Deep learning, Artificial intelligence and Machine learning. His research combines Algorithm and Artificial intelligence. The concepts of his Algorithm study are interwoven with issues in Leverage, Pixel, Invariant, Supervised learning and Differentiable function.

His biological study spans a wide range of topics, including Augmented reality and Image compression. His Pyramid study combines topics from a wide range of disciplines, such as Image processing, Range and Pyramid. Key and Image are two areas of study in which Yuri Boykov engages in interdisciplinary work.

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.

Top Publications

Fast approximate energy minimization via graph cuts

Y. Boykov;O. Veksler;R. Zabih.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)

9991 Citations

Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images

Y.Y. Boykov;M.-P. Jolly.
international conference on computer vision (2001)

6221 Citations

An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision

Y. Boykov;V. Kolmogorov.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

5919 Citations

Graph Cuts and Efficient N-D Image Segmentation

Yuri Boykov;Gareth Funka-Lea.
International Journal of Computer Vision (2006)

2533 Citations

Markov random fields with efficient approximations

Y. Boykov;O. Veksler;R. Zabih.
computer vision and pattern recognition (1998)

719 Citations

Fast approximate energy minimization with label costs

Andrew Delong;Anton Osokin;Hossam N. Isack;Yuri Boykov.
computer vision and pattern recognition (2010)

626 Citations

Superpixels and supervoxels in an energy optimization framework

Olga Veksler;Yuri Boykov;Paria Mehrani.
european conference on computer vision (2010)

543 Citations

Interactive Organ Segmentation Using Graph Cuts

Yuri Boykov;Marie-Pierre Jolly.
medical image computing and computer assisted intervention (2000)

373 Citations

Energy-Based Geometric Multi-model Fitting

Hossam Isack;Yuri Boykov.
International Journal of Computer Vision (2012)

307 Citations

Graph Cuts in Vision and Graphics: Theories and Applications

Yuri Boykov;Olga Veksler.
Handbook of Mathematical Models in Computer Vision (2006)

277 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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