What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Hong-Jiang Zhang mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Information retrieval.
Within one scientific family, Hong-Jiang Zhang focuses on topics pertaining to Machine learning under Artificial intelligence, and may sometimes address concerns connected to Standard test image.
His work carried out in the field of Pattern recognition brings together such families of science as Subspace topology, Facial recognition system, Face detection and Feature.
His Image retrieval study combines topics from a wide range of disciplines, such as Contextual image classification and Color histogram.
His study in Information retrieval is interdisciplinary in nature, drawing from both Annotation, Data mining and Visual Word.
His work deals with themes such as Multimedia, Motion compensation, Parsing and Video processing, which intersect with Video tracking.
His most cited work include:
- Face recognition using Laplacianfaces (2852 citations)
- Graph Embedding and Extensions: A General Framework for Dimensionality Reduction (2213 citations)
- Automatic partitioning of full-motion video (1256 citations)
What are the main themes of his work throughout his whole career to date?
Hong-Jiang Zhang focuses on Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Information retrieval.
His research in Artificial intelligence focuses on subjects like Machine learning, which are connected to Probabilistic logic.
The concepts of his Pattern recognition study are interwoven with issues in Face detection, Speech recognition, Feature and Cluster analysis.
Image retrieval is frequently linked to Data mining in his study.
His Information retrieval research incorporates elements of Annotation and Image.
His Video tracking research is multidisciplinary, incorporating perspectives in Multimedia, Parsing and Video processing.
He most often published in these fields:
- Artificial intelligence (58.98%)
- Pattern recognition (33.88%)
- Computer vision (30.00%)
What were the highlights of his more recent work (between 2007-2017)?
- Artificial intelligence (58.98%)
- Information retrieval (22.45%)
- Pattern recognition (33.88%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Information retrieval, Pattern recognition, Image retrieval and Machine learning.
Artificial intelligence is often connected to Computer vision in his work.
His Information retrieval research includes elements of Social media and Image.
His biological study deals with issues like Iterative reconstruction, which deal with fields such as Subspace topology.
His studies in Image retrieval integrate themes in fields like Visualization, Data mining and Cluster analysis.
His Machine learning study integrates concerns from other disciplines, such as Probabilistic logic, Cognitive neuroscience of visual object recognition and Data set.
Between 2007 and 2017, his most popular works were:
- Tag ranking (456 citations)
- Towards a Relevant and Diverse Search of Social Images (213 citations)
- Multi-label sparse coding for automatic image annotation (198 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His main research concerns Information retrieval, Search engine indexing, Image retrieval, Artificial intelligence and Ranking.
His Information retrieval research is multidisciplinary, relying on both Ranking and Image.
Hong-Jiang Zhang interconnects Tag cloud, Semantic similarity and Feature in the investigation of issues within Search engine indexing.
His Artificial intelligence research integrates issues from Machine learning and Pattern recognition.
The various areas that Hong-Jiang Zhang examines in his Pattern recognition study include Contextual image classification, Iterative reconstruction and Image processing.
His biological study spans a wide range of topics, including Social media, Similarity, Relevance and Visualization.
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