H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 31 Citations 3,891 143 World Ranking 7947 National Ranking 104

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Machine learning

Ngai-Man Cheung mainly focuses on Artificial intelligence, Pattern recognition, Artificial neural network, Computer vision and Real-time computing. Within one scientific family, he focuses on topics pertaining to Machine learning under Artificial intelligence, and may sometimes address concerns connected to Pooling. His Pattern recognition study incorporates themes from Transform coding and Feature.

His Artificial neural network study deals with Network model intersecting with Theoretical computer science. His work in Computer vision tackles topics such as Visual search which are related to areas like Multimedia. His study in Real-time computing is interdisciplinary in nature, drawing from both Goodput, Multiview Video Coding, Forward error correction and Computer network, Server.

His most cited work include:

  • Mobile Visual Search (321 citations)
  • Interactive Streaming of Stored Multiview Video Using Redundant Frame Structures (108 citations)
  • The stanford mobile visual search data set (107 citations)

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

Ngai-Man Cheung mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Algorithm and Hash function. His research brings together the fields of Machine learning and Artificial intelligence. Ngai-Man Cheung interconnects Embedding and Autoencoder in the investigation of issues within Pattern recognition.

His work in the fields of Algorithm, such as Distributed source coding, Decoding methods and Data compression, overlaps with other areas such as Encoder. The concepts of his Distributed source coding study are interwoven with issues in Multiview Video Coding, Real-time computing, Wavelet and Context-adaptive binary arithmetic coding. His Hash function research focuses on Image retrieval and how it connects with Convolutional neural network.

He most often published in these fields:

  • Artificial intelligence (57.21%)
  • Pattern recognition (24.65%)
  • Computer vision (22.33%)

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

  • Artificial intelligence (57.21%)
  • Pattern recognition (24.65%)
  • Algorithm (19.07%)

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

Artificial intelligence, Pattern recognition, Algorithm, Image retrieval and Hash function are his primary areas of study. His Artificial intelligence study frequently draws connections between adjacent fields such as Machine learning. His study ties his expertise on Pixel together with the subject of Pattern recognition.

His Algorithm research is multidisciplinary, incorporating elements of Discriminator, Embedding, Autoencoder and Point cloud. His Image retrieval research incorporates themes from Convolutional neural network and Feature. His work is dedicated to discovering how Hash function, Benchmark are connected with Pose, RANSAC, Computer vision, Modality and Word and other disciplines.

Between 2017 and 2021, his most popular works were:

  • Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study (65 citations)
  • Efficient and Deep Person Re-identification Using Multi-level Similarity (43 citations)
  • Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding (38 citations)

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

  • Artificial intelligence
  • Algorithm
  • Machine learning

Ngai-Man Cheung mostly deals with Artificial intelligence, Pattern recognition, Algorithm, Autoencoder and Image retrieval. His Artificial intelligence study frequently draws connections between related disciplines such as Machine learning. As a member of one scientific family, Ngai-Man Cheung mostly works in the field of Pattern recognition, focusing on Transformer and, on occasion, Visualization.

Ngai-Man Cheung has researched Algorithm in several fields, including Artificial neural network, Embedding, Point cloud and Outlier. His work carried out in the field of Autoencoder brings together such families of science as Focus, False positive paradox, Anomaly detection and Pipeline. As a part of the same scientific study, Ngai-Man Cheung usually deals with the Image retrieval, concentrating on Hash function and frequently concerns with RANSAC, Pose and Benchmark.

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

Mobile Visual Search

B Girod;V Chandrasekhar;D M Chen;Ngai-Man Cheung.
IEEE Signal Processing Magazine (2011)

393 Citations

The stanford mobile visual search data set

Vijay R. Chandrasekhar;David M. Chen;Sam S. Tsai;Ngai-Man Cheung.
acm sigmm conference on multimedia systems (2011)

166 Citations

Interactive Streaming of Stored Multiview Video Using Redundant Frame Structures

G Cheung;A Ortega;Ngai-Man Cheung.
IEEE Transactions on Image Processing (2011)

152 Citations

Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study

Bach Xuan Tran;Bach Xuan Tran;Giang Thu Vu;Giang Hai Ha;Quan Hoang Vuong.
Journal of Clinical Medicine (2019)

137 Citations

Learning to Hash with Binary Deep Neural Network

Thanh-Toan Do;Anh-Dzung Doan;Ngai-Man Cheung.
european conference on computer vision (2016)

129 Citations

Mobile product recognition

Sam S. Tsai;David Chen;Vijay Chandrasekhar;Gabriel Takacs.
acm multimedia (2010)

92 Citations

Enabling Adaptive High-Frame-Rate Video Streaming in Mobile Cloud Gaming Applications

Jiyan Wu;Chau Yuen;Ngai-Man Cheung;Junliang Chen.
IEEE Transactions on Circuits and Systems for Video Technology (2015)

81 Citations

Efficient wavelet-based predictive Slepian-Wolf coding for hyperspectral imagery

Ngai-Man Cheung;Caimu Tang;Antonio Ortega;Cauligi S. Raghavendra.
Signal Processing (2006)

79 Citations

Distributed source coding techniques for interactive multiview video streaming

Ngai-Man Cheung;Antonio Ortega;Gene Cheung.
picture coding symposium (2009)

79 Citations

Image-based vehicle analysis using deep neural network: A systematic study

Yiren Zhou;Hossein Nejati;Thanh-Toan Do;Ngai-Man Cheung.
international conference on digital signal processing (2016)

74 Citations

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Best Scientists Citing Ngai-Man Cheung

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Pascal Frossard

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Gene Cheung

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Bernd Girod

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David Chen

United States National Library of Medicine

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Wen Gao

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Chinese University of Hong Kong, Shenzhen

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Feng Wu

University of Science and Technology of China

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Google (Switzerland)

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Beatrice Pesquet-Popescu

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Radek Grzeszczuk

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