H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 32 Citations 5,034 174 World Ranking 7478 National Ranking 708

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Algorithm

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Motion estimation. In general Artificial intelligence study, his work on Image segmentation and Video tracking often relates to the realm of Speedup, Reference frame and Graph, thereby connecting several areas of interest. His work on Detection performance expands to the thematically related Computer vision.

His research in Pattern recognition intersects with topics in Histogram, Image and Object detection, Kadir–Brady saliency detector. His Motion estimation study combines topics in areas such as Macroblock, Multiview Video Coding and Image processing. His studies deal with areas such as Motion vector and Algorithmic efficiency as well as Algorithm.

His most cited work include:

  • An Effective CU Size Decision Method for HEVC Encoders (351 citations)
  • Saliency Tree: A Novel Saliency Detection Framework (202 citations)
  • Effective CU Size Decision for HEVC Intracoding (166 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, Segmentation and Image segmentation. Image, Saliency map, Object, Feature extraction and Pixel are among the areas of Artificial intelligence where the researcher is concentrating his efforts. In his research, Gaze and Salient is intimately related to Salience, which falls under the overarching field of Computer vision.

Zhi Liu works mostly in the field of Pattern recognition, limiting it down to topics relating to Feature and, in certain cases, RGB color model, as a part of the same area of interest. His work deals with themes such as Video tracking, Pascal and Fixation, which intersect with Segmentation. His work on Image texture is typically connected to Kernel density estimation as part of general Image segmentation study, connecting several disciplines of science.

He most often published in these fields:

  • Artificial intelligence (87.02%)
  • Computer vision (54.33%)
  • Pattern recognition (53.85%)

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

  • Artificial intelligence (87.02%)
  • Pattern recognition (53.85%)
  • Segmentation (30.77%)

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

Zhi Liu mostly deals with Artificial intelligence, Pattern recognition, Segmentation, Image and Convolutional neural network. His research ties Computer vision and Artificial intelligence together. Zhi Liu interconnects Salient, Benchmark and Salience in the investigation of issues within Computer vision.

His work on Feature extraction as part of general Pattern recognition study is frequently connected to Modal, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Segmentation research also works with subjects such as

  • Pascal which connect with Training set,
  • Fixation and related Representation. His work on Color image as part of general Image research is often related to Structure and Division, thus linking different fields of science.

Between 2017 and 2021, his most popular works were:

  • Cross-Modal Self-Attention Network for Referring Image Segmentation (63 citations)
  • ICNet: Information Conversion Network for RGB-D Based Salient Object Detection (35 citations)
  • Improving Video Saliency Detection via Localized Estimation and Spatiotemporal Refinement (27 citations)

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

  • Artificial intelligence
  • Computer vision
  • Algorithm

Zhi Liu mainly investigates Artificial intelligence, Pattern recognition, Convolutional neural network, Saliency map and Segmentation. Zhi Liu has included themes like Machine learning and Computer vision in his Artificial intelligence study. His Computer vision study frequently draws connections to adjacent fields such as Robustness.

His Pattern recognition research incorporates elements of Artificial neural network, Object and Image. His Saliency map study combines topics from a wide range of disciplines, such as Motion and Salient objects. His biological study focuses on Image 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

An Effective CU Size Decision Method for HEVC Encoders

Liquan Shen;Zhi Liu;Xinpeng Zhang;Wenqiang Zhao.
IEEE Transactions on Multimedia (2013)

467 Citations

Saliency Tree: A Novel Saliency Detection Framework

Zhi Liu;Wenbin Zou;Olivier Le Meur.
IEEE Transactions on Image Processing (2014)

242 Citations

Effective CU Size Decision for HEVC Intracoding

Liquan Shen;Zhaoyang Zhang;Zhi Liu.
IEEE Transactions on Image Processing (2014)

217 Citations

Superpixel-Based Spatiotemporal Saliency Detection

Zhi Liu;Xiang Zhang;Shuhua Luo;Olivier Le Meur.
IEEE Transactions on Circuits and Systems for Video Technology (2014)

204 Citations

Adaptive Inter-Mode Decision for HEVC Jointly Utilizing Inter-Level and Spatiotemporal Correlations

Liquan Shen;Zhaoyang Zhang;Zhi Liu.
IEEE Transactions on Circuits and Systems for Video Technology (2014)

194 Citations

Mean shift blob tracking with kernel histogram filtering and hypothesis testing

Ning Song Peng;Jie Yang;Zhi Liu.
Pattern Recognition Letters (2005)

158 Citations

Saccadic model of eye movements for free-viewing condition.

Olivier Le Meur;Zhi Liu.
Vision Research (2015)

146 Citations

Co-Saliency Detection Based on Hierarchical Segmentation

Zhi Liu;Wenbin Zou;Lina Li;Liquan Shen.
IEEE Signal Processing Letters (2014)

144 Citations

Unsupervised Salient Object Segmentation Based on Kernel Density Estimation and Two-Phase Graph Cut

Zhi Liu;Ran Shi;Liquan Shen;Yinzhu Xue.
IEEE Transactions on Multimedia (2012)

142 Citations

Depth-Aware Salient Object Detection and Segmentation via Multiscale Discriminative Saliency Fusion and Bootstrap Learning

Hangke Song;Zhi Liu;Huan Du;Guangling Sun.
IEEE Transactions on Image Processing (2017)

140 Citations

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