What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Shijian Lu focuses on Artificial intelligence, Computer vision, Pattern recognition, Pixel and Image segmentation.
His Artificial intelligence research is multidisciplinary, relying on both Speech recognition and Natural language processing.
His Edge detection study, which is part of a larger body of work in Computer vision, is frequently linked to Iterative method, bridging the gap between disciplines.
His work on Discriminative model as part of general Pattern recognition study is frequently connected to Consistency, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Pixel research includes themes of Feature detection and Optic disc.
His Feature detection study incorporates themes from Image restoration, Data mining and Image texture.
His most cited work include:
- ICDAR 2015 competition on Robust Reading (541 citations)
- Robust Document Image Binarization Technique for Degraded Document Images (198 citations)
- Binarization of historical document images using the local maximum and minimum (192 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Pixel.
His study in Image, Image segmentation, Feature extraction, Discriminative model and Feature is carried out as part of his Artificial intelligence studies.
The Computer vision study combines topics in areas such as Retinal, Optic disc and Support vector machine.
His work in Pattern recognition covers topics such as Contextual image classification which are related to areas like Scale-invariant feature transform.
His Segmentation research incorporates themes from Bilateral filter, Speech recognition and Feature vector.
His Pixel research integrates issues from Brightness, Image restoration and Feature detection.
He most often published in these fields:
- Artificial intelligence (88.37%)
- Computer vision (49.77%)
- Pattern recognition (46.98%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (88.37%)
- Pattern recognition (46.98%)
- Image (14.42%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Pattern recognition, Image, Computer vision and Feature are his primary areas of study.
His research combines Machine learning and Artificial intelligence.
Shijian Lu combines subjects such as Object detection and Facial expression with his study of Pattern recognition.
His research on Facial expression also deals with topics like
- Ranking that connect with fields like Facial expression recognition and Facial recognition system,
- Minification, Image segmentation and Contextual image classification most often made with reference to Focus.
Shijian Lu focuses mostly in the field of Computer vision, narrowing it down to matters related to Light intensity and, in some cases, 3D rendering and Computer graphics.
His Segmentation study combines topics from a wide range of disciplines, such as Entropy and Point.
Between 2019 and 2021, his most popular works were:
- AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-Identification (33 citations)
- Suppressing Uncertainties for Large-Scale Facial Expression Recognition (28 citations)
- Cascade EF-GAN: Progressive Facial Expression Editing With Local Focuses (14 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Shijian Lu mostly deals with Artificial intelligence, Pattern recognition, Image, Computer vision and Machine learning.
His studies deal with areas such as Focus and Adaptation as well as Artificial intelligence.
His studies in Pattern recognition integrate themes in fields like Feature and Hyperspectral image classification.
His research in Image intersects with topics in Segmentation, Shadow and Task.
His work in the fields of Computer vision, such as Object, Projector and 3D rendering, overlaps with other areas such as Distribution.
The various areas that Shijian Lu examines in his Machine learning study include Brainstorming and Pose.
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