What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Guojun Lu mainly focuses on Artificial intelligence, Image retrieval, Computer vision, Pattern recognition and Content-based image retrieval.
Guojun Lu focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Curvature and, in some cases, Algorithm, Gaussian blur, Image sensor and Pixel.
His Image retrieval research also works with subjects such as
- Information retrieval most often made with reference to Feature extraction,
- Feature that intertwine with fields like Image.
Guojun Lu works mostly in the field of Computer vision, limiting it down to topics relating to Representation and, in certain cases, Computation, as a part of the same area of interest.
His study in the field of Heat kernel signature, Active shape model, Shape analysis and Gabor filter also crosses realms of Gabor wavelet.
The Content-based image retrieval study combines topics in areas such as Normalization and Similitude.
His most cited work include:
- Review of shape representation and description techniques (1547 citations)
- A survey of content-based image retrieval with high-level semantics (1366 citations)
- Shape-based image retrieval using generic Fourier descriptor (443 citations)
What are the main themes of his work throughout his whole career to date?
Guojun Lu mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Visual Word.
His Pattern recognition research includes elements of Contextual image classification, Image, Invariant and Feature.
Guojun Lu has researched Computer vision in several fields, including Curvature and Robustness.
His Image retrieval study also includes
- Information retrieval which is related to area like Semantics,
- Search engine indexing which is related to area like Vector quantization.
His Visual Word research incorporates elements of Image segmentation and Automatic image annotation.
His studies deal with areas such as Feature detection and Semantic gap as well as Automatic image annotation.
He most often published in these fields:
- Artificial intelligence (69.29%)
- Pattern recognition (45.64%)
- Computer vision (43.57%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (69.29%)
- Pattern recognition (45.64%)
- Computer vision (43.57%)
In recent papers he was focusing on the following fields of study:
Guojun Lu focuses on Artificial intelligence, Pattern recognition, Computer vision, Histogram and Benchmark.
His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Machine learning.
His Pattern recognition research includes elements of Contextual image classification, Image and Invariant.
The various areas that he examines in his Computer vision study include Lidar and Curvature.
His work deals with themes such as Similarity and Feature, which intersect with Benchmark.
As part of one scientific family, Guojun Lu deals mainly with the area of Image retrieval, narrowing it down to issues related to the Measure, and often Similarity and Similarity measure.
Between 2014 and 2021, his most popular works were:
- An automatic building extraction and regularisation technique using LiDAR point cloud data and orthoimage (56 citations)
- Segmentation of Airborne Point Cloud Data for Automatic Building Roof Extraction (21 citations)
- Effective and efficient contour-based corner detectors (20 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Artificial intelligence, Computer vision, Pattern recognition, Point cloud and Histogram are his primary areas of study.
His Artificial intelligence study typically links adjacent topics like Remote sensing.
His Segmentation, Image registration and Scale-invariant feature transform study, which is part of a larger body of work in Computer vision, is frequently linked to Terrain, bridging the gap between disciplines.
His biological study focuses on Feature extraction.
His Histogram study combines topics in areas such as Image histogram, Image texture, Invariant, Automatic image annotation and Visual Word.
Guojun Lu has researched Image segmentation in several fields, including Rectangle, Image compression, Cuboid, Search engine indexing and Image retrieval.
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