H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 62 Citations 16,945 470 World Ranking 1406 National Ranking 133

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Feature extraction are his primary areas of study. His study in Feature, Robustness, Contextual image classification, Segmentation and Image segmentation is carried out as part of his studies in Artificial intelligence. His work carried out in the field of Pattern recognition brings together such families of science as Facial recognition system and Cluster analysis.

His work on Matching, Pixel, Gesture and Gesture recognition as part of general Computer vision study is frequently connected to Ball, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. Hanqing Lu interconnects Subspace topology and The Internet in the investigation of issues within Machine learning. His Feature extraction study incorporates themes from Video tracking, Speech recognition, Similarity and Reliability.

His most cited work include:

  • Unsupervised feature selection using nonnegative spectral analysis (315 citations)
  • Face detection using improved LBP under Bayesian framework (292 citations)
  • A nonlinear approach for face sketch synthesis and recognition (279 citations)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Feature extraction. All of his Artificial intelligence and Discriminative model, Image segmentation, Feature, Segmentation and Facial recognition system investigations are sub-components of the entire Artificial intelligence study. His Facial recognition system research is multidisciplinary, relying on both Subspace topology and Kernel.

His Pattern recognition research is multidisciplinary, incorporating elements of Contextual image classification, Histogram, Image and Cluster analysis. His study ties his expertise on Robustness together with the subject of Computer vision. The various areas that he examines in his Machine learning study include Classifier, Data mining and Image retrieval.

He most often published in these fields:

  • Artificial intelligence (76.33%)
  • Pattern recognition (43.59%)
  • Computer vision (35.70%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (76.33%)
  • Pattern recognition (43.59%)
  • Machine learning (18.54%)

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

Hanqing Lu focuses on Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Discriminative model. Feature, Segmentation, Convolutional neural network, Feature extraction and Object are the core of his Artificial intelligence study. His studies in Pattern recognition integrate themes in fields like Contextual image classification, Image, Face and Cluster analysis.

Inference is closely connected to Question answering in his research, which is encompassed under the umbrella topic of Machine learning. His Computer vision study combines topics in areas such as Robustness and Benchmark. His Discriminative model research is multidisciplinary, incorporating perspectives in Feature, Constraint and Set.

Between 2014 and 2021, his most popular works were:

  • Robust Structured Subspace Learning for Data Representation (259 citations)
  • Stacked Deconvolutional Network for Semantic Segmentation (104 citations)
  • Online sketching hashing (77 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Hanqing Lu mainly investigates Artificial intelligence, Pattern recognition, Feature, Machine learning and Convolutional neural network. His Artificial intelligence study frequently intersects with other fields, such as Computer vision. His research integrates issues of Contextual image classification, Structure and Benchmark in his study of Pattern recognition.

The concepts of his Feature study are interwoven with issues in Deep learning, Non-negative matrix factorization, Feature vector and Compression. His work on Cluster analysis as part of general Machine learning study is frequently linked to Locality-sensitive hashing, Hash table and Feature hashing, therefore connecting diverse disciplines of science. His Convolutional neural network study integrates concerns from other disciplines, such as Compression method, Recurrent neural network and Feature.

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

Face detection using improved LBP under Bayesian framework

Hongliang Jin;Qingshan Liu;Hanqing Lu;Xiaofeng Tong.
international conference on image and graphics (2004)

455 Citations

Solving the small sample size problem of LDA

Rui Huang;Qingshan Liu;Hanqing Lu;Songde Ma.
international conference on pattern recognition (2002)

425 Citations

A nonlinear approach for face sketch synthesis and recognition

Qingshan Liu;Xiaoou Tang;Hongliang Jin;Hanqing Lu.
computer vision and pattern recognition (2005)

374 Citations

Street-to-shop: cross-scenario clothing retrieval via parts alignment and auxiliary set

Si Liu;Zheng Song;Meng Wang;Changsheng Xu.
acm multimedia (2012)

357 Citations

Unsupervised feature selection using nonnegative spectral analysis

Zechao Li;Yi Yang;Jing Liu;Xiaofang Zhou.
national conference on artificial intelligence (2012)

351 Citations

Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set

Si Liu;Zheng Song;Guangcan Liu;Changsheng Xu.
computer vision and pattern recognition (2012)

351 Citations

Robust Structured Subspace Learning for Data Representation

Zechao Li;Jing Liu;Jinhui Tang;Hanqing Lu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2015)

314 Citations

Hi, magic closet, tell me what to wear!

Si Liu;Jiashi Feng;Zheng Song;Tianzhu Zhang.
acm multimedia (2012)

276 Citations

Clustering-Guided Sparse Structural Learning for Unsupervised Feature Selection

Zechao Li;Jing Liu;Yi Yang;Xiaofang Zhou.
IEEE Transactions on Knowledge and Data Engineering (2014)

272 Citations

Image annotation via graph learning

Jing Liu;Mingjing Li;Qingshan Liu;Hanqing Lu.
Pattern Recognition (2009)

268 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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Top Scientists Citing Hanqing Lu

Shuicheng Yan

Shuicheng Yan

National University of Singapore

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Qi Tian

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Huawei Technologies (China)

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Chinese Academy of Sciences

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Xinbo Gao

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Chongqing University of Posts and Telecommunications

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Xuelong Li

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Northwestern Polytechnical University

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Jinhui Tang

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Nanjing University of Science and Technology

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Dacheng Tao

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University of Sydney

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Nannan Wang

Nannan Wang

Xidian University

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Changsheng Xu

Changsheng Xu

Chinese Academy of Sciences

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Meng Wang

Meng Wang

Hefei University of Technology

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Tao Mei

Tao Mei

Jingdong (China)

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Zechao Li

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Nanjing University of Science and Technology

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Ling Shao

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Inception Institute of Artificial Intelligence

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Jian Cheng

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Wen Gao

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