D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 55 Citations 11,334 215 World Ranking 2166 National Ranking 1181

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Shape analysis and Active shape model. His study ties his expertise on Graph theory together with the subject of Artificial intelligence. His Pattern recognition study combines topics in areas such as Graph, Shape context and Image retrieval.

As part of the same scientific family, he usually focuses on Computer vision, concentrating on Computational geometry and intersecting with Connected component, Background subtraction and Simple. In Shape analysis, Longin Jan Latecki works on issues like Discriminative model, which are connected to Video tracking, Search engine indexing, Coding and Feature vector. His biological study deals with issues like Scaling, which deal with fields such as Smoothing, Tangent, Invariant and Transformation geometry.

His most cited work include:

  • Shape descriptors for non-rigid shapes with a single closed contour (720 citations)
  • Shape similarity measure based on correspondence of visual parts (412 citations)
  • Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution (367 citations)

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

Longin Jan Latecki focuses on Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Segmentation. His work investigates the relationship between Artificial intelligence and topics such as Graph that intersect with problems in Theoretical computer science. His Computer vision study focuses mostly on Digitization, Digital image, Object, Shape analysis and Motion detection.

His research ties Topology and Digitization together. His Pattern recognition research is multidisciplinary, relying on both Image, Similarity and Image retrieval. His work deals with themes such as Particle filter and Topological skeleton, which intersect with Algorithm.

He most often published in these fields:

  • Artificial intelligence (68.55%)
  • Computer vision (37.81%)
  • Pattern recognition (34.98%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (68.55%)
  • Pattern recognition (34.98%)
  • Segmentation (8.83%)

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

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Segmentation, Computer vision and Convolutional neural network. He studied Artificial intelligence and Machine learning that intersect with Graph. The study incorporates disciplines such as Pixel, Visualization, Pascal and Saliency map in addition to Pattern recognition.

His Segmentation study integrates concerns from other disciplines, such as Encoder, Pyramid and Conditional random field. Longin Jan Latecki regularly ties together related areas like Location aware in his Computer vision studies. His Convolutional neural network research incorporates elements of Recurrent neural network, Image, Polygon mesh and Parsing.

Between 2015 and 2021, his most popular works were:

  • GIFT: A Real-Time and Scalable 3D Shape Search Engine (124 citations)
  • Amodal Detection of 3D Objects: Inferring 3D Bounding Boxes from 2D Ones in RGB-Depth Images (74 citations)
  • DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks. (71 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Segmentation, Computer vision and Feature extraction. His Artificial intelligence research includes themes of Graph and Data mining. Longin Jan Latecki has researched Pattern recognition in several fields, including Pixel and Machine learning.

His Segmentation research includes themes of Encoder, Decoding methods, Communication channel and Computer engineering. In general Computer vision, his work in Visual appearance, Channel and RGB color model is often linked to Amodal perception linking many areas of study. His Feature extraction research incorporates elements of Inverted index, Scalability, Feature and Projection.

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.

Best Publications

Shape descriptors for non-rigid shapes with a single closed contour

L.J. Latecki;R. Lakamper;T. Eckhardt.
computer vision and pattern recognition (2000)

1052 Citations

Shape similarity measure based on correspondence of visual parts

L.J. Latecki;R. Lakamper.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2000)

650 Citations

Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution

Xiang Bai;L.J. Latecki;Wen-Yu Liu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

545 Citations

Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution

Longin Jan Latecki;Rolf Lakämper.
Computer Vision and Image Understanding (1999)

499 Citations

Path Similarity Skeleton Graph Matching

Xiang Bai;L.J. Latecki.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

485 Citations

Incremental Local Outlier Detection for Data Streams

D. Pokrajac;A. Lazarevic;L.J. Latecki.
computational intelligence and data mining (2007)

467 Citations

Learning Context-Sensitive Shape Similarity by Graph Transduction

Xiang Bai;Xingwei Yang;L.J. Latecki;Wenyu Liu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

334 Citations

Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval

Xingwei Yang;Suzan Koknar-Tezel;Longin Jan Latecki.
computer vision and pattern recognition (2009)

242 Citations

Maximum weight cliques with mutex constraints for video object segmentation

Tianyang Ma;Longin Jan Latecki.
computer vision and pattern recognition (2012)

238 Citations

Outlier Detection with Kernel Density Functions

Longin Jan Latecki;Aleksandar Lazarevic;Dragoljub Pokrajac.
machine learning and data mining in pattern recognition (2007)

214 Citations

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