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 33 Citations 5,402 293 World Ranking 6829 National Ranking 58

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 investigation include Artificial intelligence, Computer vision, Pattern recognition, Stereoscopy and Visualization. His Artificial intelligence research focuses on Iterative reconstruction, Autostereoscopy, Stereo display, Depth map and Rendering. His Computer vision study frequently draws connections to other fields, such as Interpolation.

His study looks at the intersection of Pattern recognition and topics like Image with Pooling. His research in Stereoscopy intersects with topics in Image quality, Visual perception and Metric. His Image processing research includes themes of Smoothing, Linear system and Computer graphics.

His most cited work include:

  • Fast global image smoothing based on weighted least squares. (206 citations)
  • Gradient-Enhancing Conversion for Illumination-Robust Lane Detection (129 citations)
  • Cost Aggregation and Occlusion Handling With WLS in Stereo Matching (127 citations)

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

Kwanghoon Sohn spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Pixel. His study in Artificial intelligence focuses on Convolutional neural network, Image, Feature, Feature extraction and Robustness. His Computer vision study often links to related topics such as Computer graphics.

His Pattern recognition study integrates concerns from other disciplines, such as Matching and Depth map. His study explores the link between Algorithm and topics such as Coding that cross with problems in Multiview Video Coding. The study incorporates disciplines such as Pose and Invariant in addition to Facial recognition system.

He most often published in these fields:

  • Artificial intelligence (81.33%)
  • Computer vision (60.44%)
  • Pattern recognition (26.04%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (81.33%)
  • Pattern recognition (26.04%)
  • Convolutional neural network (9.58%)

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

Kwanghoon Sohn focuses on Artificial intelligence, Pattern recognition, Convolutional neural network, Computer vision and Feature extraction. His studies deal with areas such as Matching and Machine learning as well as Artificial intelligence. His Pattern recognition research includes elements of Inference, Leverage, Transformer and Stereo matching.

His research integrates issues of Object detection, Iterative reconstruction, Unsupervised learning, Supervised learning and Kernel in his study of Convolutional neural network. The Computer vision study which covers Mobile device that intersects with Lidar. The various areas that Kwanghoon Sohn examines in his Feature extraction study include Visualization and Embedding.

Between 2016 and 2021, his most popular works were:

  • FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence (69 citations)
  • Recurrent Transformer Networks for Semantic Correspondence (56 citations)
  • Unified Confidence Estimation Networks for Robust Stereo Matching (28 citations)

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

  • Artificial intelligence
  • Computer vision
  • Statistics

Kwanghoon Sohn mainly investigates Artificial intelligence, Pattern recognition, Convolutional neural network, Computer vision and Feature extraction. As part of one scientific family, Kwanghoon Sohn deals mainly with the area of Artificial intelligence, narrowing it down to issues related to the Matching, and often Depth map. He interconnects Transformer, Deep neural networks, Pixel, Image and RGB color model in the investigation of issues within Pattern recognition.

His Convolutional neural network study combines topics from a wide range of disciplines, such as Channel, Supervised learning, Unsupervised learning and Iterative reconstruction. Kwanghoon Sohn is involved in the study of Computer vision that focuses on Image processing in particular. While the research belongs to areas of Feature extraction, Kwanghoon Sohn spends his time largely on the problem of Emotion recognition, intersecting his research to questions surrounding Facial expression, Visualization, Face and Facial recognition system.

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

Fast global image smoothing based on weighted least squares.

Dongbo Min;Sunghwan Choi;Jiangbo Lu;Bumsub Ham.
IEEE Transactions on Image Processing (2014)

273 Citations

Gradient-Enhancing Conversion for Illumination-Robust Lane Detection

Hunjae Yoo;Ukil Yang;Kwanghoon Sohn.
IEEE Transactions on Intelligent Transportation Systems (2013)

218 Citations

Real-time illumination invariant lane detection for lane departure warning system

Jongin Son;Hunjae Yoo;Sanghoon Kim;Kwanghoon Sohn.
Expert Systems With Applications (2015)

206 Citations

Apparatus for encoding a multi-view moving picture

Kwang Hoon Sohn;Jeong Eun Lim;Byeong Ho Choi;Je Woo Kim.
(2002)

191 Citations

Cost Aggregation and Occlusion Handling With WLS in Stereo Matching

Dongbo Min;Kwanghoon Sohn.
IEEE Transactions on Image Processing (2008)

160 Citations

Visual Fatigue Prediction for Stereoscopic Image

Donghyun Kim;Kwanghoon Sohn.
IEEE Transactions on Circuits and Systems for Video Technology (2011)

144 Citations

Deinterlacing using directional interpolation and motion compensation

O. Kwon;Kwanghoon Sohn;Chulhee Lee.
IEEE Transactions on Consumer Electronics (2003)

125 Citations

No-Reference Quality Assessment for Stereoscopic Images Based on Binocular Quality Perception

Seungchul Ryu;Kwanghoon Sohn.
IEEE Transactions on Circuits and Systems for Video Technology (2014)

118 Citations

FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence

Seungryong Kim;Dongbo Min;Bumsub Ham;Stephen Lin.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2019)

116 Citations

A Stereoscopic Video Generation Method Using Stereoscopic Display Characterization and Motion Analysis

Donghyun Kim;Dongbo Min;Kwanghoon Sohn.
IEEE Transactions on Broadcasting (2008)

101 Citations

Best Scientists Citing Kwanghoon Sohn

Alan C. Bovik

Alan C. Bovik

The University of Texas at Austin

Publications: 22

Weisi Lin

Weisi Lin

Nanyang Technological University

Publications: 18

Marta Karczewicz

Marta Karczewicz

Qualcomm (United Kingdom)

Publications: 17

Feng Wu

Feng Wu

University of Science and Technology of China

Publications: 16

Ying Chen

Ying Chen

Qualcomm (United Kingdom)

Publications: 16

Stefano Mattoccia

Stefano Mattoccia

University of Bologna

Publications: 15

Minsu Cho

Minsu Cho

Pohang University of Science and Technology

Publications: 13

Yong Man Ro

Yong Man Ro

Korea Advanced Institute of Science and Technology

Publications: 13

Sanghoon Lee

Sanghoon Lee

Yonsei University

Publications: 13

King Ngi Ngan

King Ngi Ngan

University of Electronic Science and Technology of China

Publications: 13

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 12

Wen Gao

Wen Gao

Peking University

Publications: 12

Qionghai Dai

Qionghai Dai

Tsinghua University

Publications: 12

Wan-Chi Siu

Wan-Chi Siu

Hong Kong Polytechnic University

Publications: 11

Yao Zhao

Yao Zhao

Beijing Jiaotong University

Publications: 11

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

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