2023 - Research.com Computer Science in China Leader Award
2020 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to multimedia content analysis and recognition
His primary areas of investigation include Artificial intelligence, Information retrieval, Pattern recognition, Machine learning and Image retrieval. His research links Graph with Artificial intelligence. His study in the field of Relevance, Ranking and Query expansion also crosses realms of Set.
His work on Sparse approximation and Hidden Markov model as part of general Pattern recognition research is frequently linked to Locality-sensitive hashing and K-independent hashing, bridging the gap between disciplines. His work on Support vector machine as part of general Machine learning study is frequently connected to Space, TRECVID and Disease progression, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Image retrieval research integrates issues from Similitude and Search engine indexing.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Machine learning, Information retrieval and Image. His research ties Computer vision and Artificial intelligence together. Meng Wang usually deals with Pattern recognition and limits it to topics linked to Robustness and Factorization.
The study incorporates disciplines such as Representation, Data mining and Metric in addition to Machine learning. In the subject of general Information retrieval, his work in Ranking and Relevance is often linked to Scheme and Set, thereby combining diverse domains of study. Meng Wang focuses mostly in the field of Feature extraction, narrowing it down to matters related to Visualization and, in some cases, Image retrieval.
Artificial intelligence, Pattern recognition, Machine learning, Graph and Image are his primary areas of study. Artificial intelligence is frequently linked to Natural language processing in his study. His work deals with themes such as Subspace topology, Cluster analysis, Salient and Manifold, which intersect with Pattern recognition.
He combines subjects such as Embedding, Similarity, Training set and Metric with his study of Machine learning. His Graph research is multidisciplinary, incorporating perspectives in Theoretical computer science, Artificial neural network, Recommender system, Structure and Graph. Meng Wang interconnects Visualization and Benchmark in the investigation of issues within Image.
Meng Wang focuses on Artificial intelligence, Pattern recognition, Discriminative model, Robustness and Image. His Artificial intelligence research includes themes of Machine learning and Computer vision. His Machine learning study integrates concerns from other disciplines, such as Embedding and Representation.
His Pattern recognition research is multidisciplinary, relying on both Salient, Outlier, Feature and Manifold. As part of the same scientific family, Meng Wang usually focuses on Discriminative model, concentrating on Similarity learning and intersecting with Relevance, Document retrieval, Similarity and Disjoint sets. His Robustness research incorporates elements of Algorithm and Sparse approximation.
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.
Neural Graph Collaborative Filtering
Xiang Wang;Xiangnan He;Meng Wang;Fuli Feng.
international acm sigir conference on research and development in information retrieval (2019)
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He;Kuan Deng;Xiang Wang;Yan Li.
international acm sigir conference on research and development in information retrieval (2020)
Tag ranking
Dong Liu;Xian-Sheng Hua;Linjun Yang;Meng Wang.
the web conference (2009)
3-D Object Retrieval and Recognition With Hypergraph Analysis
Yue Gao;Meng Wang;Dacheng Tao;Rongrong Ji.
IEEE Transactions on Image Processing (2012)
Unified Video Annotation via Multigraph Learning
Meng Wang;Xian-Sheng Hua;Richang Hong;Jinhui Tang.
IEEE Transactions on Circuits and Systems for Video Technology (2009)
Multimodal Deep Autoencoder for Human Pose Recovery
Chaoqun Hong;Jun Yu;Jian Wan;Dacheng Tao.
IEEE Transactions on Image Processing (2015)
Crowded Scene Analysis: A Survey
Teng Li;Huan Chang;Meng Wang;Bingbing Ni.
IEEE Transactions on Circuits and Systems for Video Technology (2015)
Visual-Textual Joint Relevance Learning for Tag-Based Social Image Search
Yue Gao;Meng Wang;Zheng-Jun Zha;Jialie Shen.
IEEE Transactions on Image Processing (2013)
Multimodal Graph-Based Reranking for Web Image Search
Meng Wang;Hao Li;Dacheng Tao;Ke Lu.
IEEE Transactions on Image Processing (2012)
Street-to-shop: cross-scenario clothing retrieval via parts alignment and auxiliary set
Si Liu;Zheng Song;Meng Wang;Changsheng Xu.
acm multimedia (2012)
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