D-Index & Metrics Best Publications

D-Index & Metrics 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.

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 32 Citations 6,046 116 World Ranking 9058 National Ranking 82

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Computer graphics are his primary areas of study. Yung-Yu Chuang undertakes interdisciplinary study in the fields of Artificial intelligence and Multiple kernel learning through his works. His Image, Alpha compositing and Image-based modeling and rendering study in the realm of Computer vision interacts with subjects such as Set.

His Pattern recognition research is multidisciplinary, incorporating perspectives in Normalization and Image enhancement. As part of the same scientific family, Yung-Yu Chuang usually focuses on Feature extraction, concentrating on Pixel and intersecting with Bayesian framework, Bayesian probability and Background image. His Computer graphics study integrates concerns from other disciplines, such as Video capture and Texture.

His most cited work include:

  • A Bayesian approach to digital matting (755 citations)
  • Video matting of complex scenes (315 citations)
  • Multiple Kernel Fuzzy Clustering (230 citations)

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

His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Computer graphics and Image. His study in Convolutional neural network, Pixel, Feature extraction, Segmentation and Object are all subfields of Artificial intelligence. In the subject of general Computer vision, his work in Rendering, Stereoscopy, Optical flow and Image warping is often linked to Process, thereby combining diverse domains of study.

The Pattern recognition study combines topics in areas such as Affinity propagation, Deep learning and Feature. His research investigates the connection between Computer graphics and topics such as Shadow that intersect with problems in Compositing. His study on Similarity is often connected to Domain, Set and Layer as part of broader study in Image.

He most often published in these fields:

  • Artificial intelligence (79.34%)
  • Computer vision (58.68%)
  • Pattern recognition (22.31%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (79.34%)
  • Computer vision (58.68%)
  • Pattern recognition (22.31%)

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

His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Convolutional neural network and Image. The study of Artificial intelligence is intertwined with the study of Dynamic range in a number of ways. His research in the fields of Optical flow, Pixel, Image stabilization and Re identification overlaps with other disciplines such as Identity.

His Pattern recognition research focuses on Deep learning and how it relates to Pose, Saliency map and Discriminative model. His work focuses on many connections between Convolutional neural network and other disciplines, such as Training set, that overlap with his field of interest in Salient object detection and Classifier. His Image study combines topics in areas such as Representation, Generative grammar and Code.

Between 2017 and 2021, his most popular works were:

  • Deep Photo Enhancer: Unpaired Learning for Image Enhancement from Photographs with GANs (155 citations)
  • Deep Video Frame Interpolation Using Cyclic Frame Generation (71 citations)
  • FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation From a Single Image (60 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, Object and Computer vision. Artificial intelligence and Color filter array are two areas of study in which Yung-Yu Chuang engages in interdisciplinary work. His work deals with themes such as Normalization, Image and Deep learning, which intersect with Pattern recognition.

His Image study incorporates themes from Noise reduction and Convolutional neural network. His research integrates issues of Ranking and Pose in his study of Deep learning. Yung-Yu Chuang combines subjects such as Pascal, Minimum bounding box and Task with his study of Segmentation.

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

A Bayesian approach to digital matting

Yung-Yu Chuang;B. Curless;D.H. Salesin;R. Szeliski.
computer vision and pattern recognition (2001)

1158 Citations

Video matting of complex scenes

Yung-Yu Chuang;Aseem Agarwala;Brian Curless;David H. Salesin.
international conference on computer graphics and interactive techniques (2002)

463 Citations

Multiple Kernel Fuzzy Clustering

Hsin-Chien Huang;Yung-Yu Chuang;Chu-Song Chen.
IEEE Transactions on Fuzzy Systems (2012)

375 Citations

Shape-Preserving Half-Projective Warps for Image Stitching

Che-Han Chang;Yoichi Sato;Yung-Yu Chuang.
computer vision and pattern recognition (2014)

265 Citations

Deep Photo Enhancer: Unpaired Learning for Image Enhancement from Photographs with GANs

Yu-Sheng Chen;Yu-Ching Wang;Man-Hsin Kao;Yung-Yu Chuang.
computer vision and pattern recognition (2018)

239 Citations

Video stabilization using robust feature trajectories

Ken-Yi Lee;Yung-Yu Chuang;Bing-Yu Chen;Ming Ouhyoung.
international conference on computer vision (2009)

215 Citations

Affinity aggregation for spectral clustering

Hsin-Chien Huang;Yung-Yu Chuang;Chu-Song Chen.
computer vision and pattern recognition (2012)

189 Citations

Environment matting extensions: towards higher accuracy and real-time capture

Yung-Yu Chuang;Douglas E. Zongker;Joel Hindorff;Brian Curless.
international conference on computer graphics and interactive techniques (2000)

186 Citations

Animating pictures with stochastic motion textures

Yung-Yu Chuang;Dan B Goldman;Ke Colin Zheng;Brian Curless.
international conference on computer graphics and interactive techniques (2005)

186 Citations

Learning to Reduce Dual-Level Discrepancy for Infrared-Visible Person Re-Identification

Zhixiang Wang;Zheng Wang;Yinqiang Zheng;Yung-Yu Chuang.
computer vision and pattern recognition (2019)

179 Citations

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