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 32 Citations 6,766 266 World Ranking 7195 National Ranking 213

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary scientific interests are in Artificial intelligence, Machine learning, Data mining, Hidden Markov model and Algorithm. His work on Deep learning as part of general Artificial intelligence research is frequently linked to Predictive medicine, bridging the gap between disciplines. His biological study spans a wide range of topics, including Subspace topology and Inference.

His work carried out in the field of Data mining brings together such families of science as Pragmatics and Naive Bayes classifier. His Hidden Markov model study integrates concerns from other disciplines, such as Hidden semi-Markov model and Activity recognition. His Algorithm research includes elements of Relation and Personalization.

His most cited work include:

  • Activity recognition and abnormality detection with the switching hidden semi-Markov model (474 citations)
  • Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter (379 citations)
  • Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model (282 citations)

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

His primary areas of study are Artificial intelligence, Machine learning, Data mining, Cluster analysis and Pattern recognition. His work on Artificial intelligence deals in particular with Inference, Deep learning, Probabilistic logic, Hidden Markov model and Boltzmann machine. His Collaborative filtering, Activity recognition and Artificial neural network study in the realm of Machine learning interacts with subjects such as Structure and Data modeling.

His Data mining study incorporates themes from Context, Subspace topology, Hierarchical Dirichlet process, Mixture model and Feature selection. His work on Correlation clustering as part of general Cluster analysis research is often related to Scalability, thus linking different fields of science. His Pattern recognition research incorporates elements of Clustering high-dimensional data, Representation and Feature.

He most often published in these fields:

  • Artificial intelligence (58.77%)
  • Machine learning (40.67%)
  • Data mining (25.63%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (58.77%)
  • Machine learning (40.67%)
  • Embedding (6.13%)

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

His primary areas of investigation include Artificial intelligence, Machine learning, Embedding, Theoretical computer science and Deep learning. Dinh Phung has researched Artificial intelligence in several fields, including Data mining and Pattern recognition. His study in the fields of Reinforcement learning under the domain of Machine learning overlaps with other disciplines such as Named-entity recognition.

His research on Embedding also deals with topics like

  • Benchmark that intertwine with fields like Relation, Representation and Pairwise comparison,
  • Feature most often made with reference to Personalization. His Theoretical computer science research is multidisciplinary, incorporating perspectives in Graph, Transformer and Graph. His research integrates issues of Data point, Penalty method, Unsupervised learning and Duality in his study of Deep learning.

Between 2018 and 2021, his most popular works were:

  • A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization (77 citations)
  • An effective spatial-temporal attention based neural network for traffic flow prediction (44 citations)
  • Robust Anomaly Detection in Videos Using Multilevel Representations (16 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Dinh Phung mainly investigates Artificial intelligence, Machine learning, Theoretical computer science, Adversarial system and Transformer. His Artificial intelligence research integrates issues from Divergence and Pattern recognition. His research in Machine learning intersects with topics in Heuristics and Heuristic.

His studies in Theoretical computer science integrate themes in fields like Graph neural networks, Graph and Convolutional neural network. His Adversarial system research is multidisciplinary, incorporating elements of Classifier and Generative grammar. His Transformer study also includes

  • Image processing most often made with reference to Self attention,
  • Embedding and related Personalization, Algorithm, Feature and Relation.

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

Activity recognition and abnormality detection with the switching hidden semi-Markov model

T.V. Duong;H.H. Bui;D.Q. Phung;S. Venkatesh.
computer vision and pattern recognition (2005)

719 Citations

Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter

Ba-Ngu Vo;Ba-Tuong Vo;Dinh Phung.
IEEE Transactions on Signal Processing (2014)

539 Citations

Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model

N.T. Nguyen;D.Q. Phung;S. Venkatesh;H. Bui.
computer vision and pattern recognition (2005)

460 Citations

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View.

Wei Luo;Dinh Phung;Truyen Tran;Sunil Gupta.
Journal of Medical Internet Research (2016)

249 Citations

Predicting healthcare trajectories from medical records: A deep learning approach.

Trang Pham;Truyen Tran;Dinh Q. Phung;Svetha Venkatesh.
Journal of Biomedical Informatics (2017)

226 Citations

DeepCare: A Deep Dynamic Memory Model forźPredictive Medicine

Trang Pham;Truyen Tran;Dinh Phung;Svetha Venkatesh.
knowledge discovery and data mining (2016)

223 Citations

A novel embedding model for knowledge base completion based on convolutional neural network

Dai Quoc Nguyen;Tu Dinh Nguyen;Dat Quoc Nguyen;Dinh Q. Phung.
north american chapter of the association for computational linguistics (2018)

198 Citations

MGAN: Training Generative Adversarial Nets with Multiple Generators

Quan Hoang;Tu Dinh Nguyen;Trung Le;Dinh Phung.
international conference on learning representations (2018)

168 Citations

Affective and Content Analysis of Online Depression Communities

Thin Nguyen;Dinh Phung;Bo Dao;Svetha Venkatesh.
IEEE Transactions on Affective Computing (2014)

156 Citations

Efficient duration and hierarchical modeling for human activity recognition

Thi Duong;Dinh Phung;Hung Bui;Svetha Venkatesh.
Artificial Intelligence (2009)

138 Citations

Best Scientists Citing Dinh Phung

Svetha Venkatesh

Svetha Venkatesh

Deakin University

Publications: 46

Ba-Ngu Vo

Ba-Ngu Vo

Curtin University

Publications: 39

Ba-Tuong Vo

Ba-Tuong Vo

Curtin University

Publications: 37

Giorgio Battistelli

Giorgio Battistelli

University of Florence

Publications: 13

Ben Kröse

Ben Kröse

Amsterdam University of Applied Sciences

Publications: 12

Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

Publications: 11

Tao Xiang

Tao Xiang

University of Surrey

Publications: 11

Shaogang Gong

Shaogang Gong

Queen Mary University of London

Publications: 11

Qiang Yang

Qiang Yang

Hong Kong University of Science and Technology

Publications: 10

Quan Z. Sheng

Quan Z. Sheng

Macquarie University

Publications: 9

Xue Li

Xue Li

University of Queensland

Publications: 9

Chong-Wah Ngo

Chong-Wah Ngo

Singapore Management University

Publications: 9

Nicu Sebe

Nicu Sebe

University of Trento

Publications: 9

Fei Wang

Fei Wang

Cornell University

Publications: 9

Bing Dong

Bing Dong

Syracuse University

Publications: 9

Gal A. Kaminka

Gal A. Kaminka

Bar-Ilan University

Publications: 8

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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