What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Statistics
His primary areas of study are Artificial intelligence, Computer vision, Image quality, Distortion and Visualization.
The various areas that Guangtao Zhai examines in his Artificial intelligence study include Machine learning, Graphics, Metric and Pattern recognition.
His work on Minimum description length as part of his general Pattern recognition study is frequently connected to Basis, thereby bridging the divide between different branches of science.
His Computer vision research incorporates themes from Entropy, Video quality and Perception.
His Image quality study incorporates themes from Data mining, Image processing, Transform coding, Support vector machine and Feature extraction.
His research in Feature extraction intersects with topics in Human visual system model and Scene statistics.
His most cited work include:
- Using free energy principle for blind image quality assessment (361 citations)
- A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme. (218 citations)
- The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement (211 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Computer vision, Image quality, Pattern recognition and Distortion.
His research combines Metric and Artificial intelligence.
His research on Computer vision often connects related areas such as Algorithm.
The Image quality study which covers Histogram that intersects with Contrast.
He has included themes like Artificial neural network and Deep learning in his Pattern recognition study.
His research on Image processing focuses in particular on Digital image processing.
He most often published in these fields:
- Artificial intelligence (73.33%)
- Computer vision (52.80%)
- Image quality (30.40%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (73.33%)
- Computer vision (52.80%)
- Convolutional neural network (6.13%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Computer vision, Convolutional neural network, Pattern recognition and Image quality.
He performs multidisciplinary study on Artificial intelligence and Distortion in his works.
His studies in Computer vision integrate themes in fields like Pyramid and Visualization.
Guangtao Zhai interconnects Viewport, Weighting, Code, Feature learning and Algorithm in the investigation of issues within Convolutional neural network.
Guangtao Zhai focuses mostly in the field of Pattern recognition, narrowing it down to topics relating to Salience and, in certain cases, Saliency map.
His Image quality research includes elements of Noise, Quality assessment, Database and Human visual system model.
Between 2019 and 2021, his most popular works were:
- Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner. (76 citations)
- How is Gaze Influenced by Image Transformations? Dataset and Model (22 citations)
- Learning To Blindly Assess Image Quality In The Laboratory And Wild (15 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Statistics
Guangtao Zhai focuses on Artificial intelligence, Computer vision, Image quality, Artificial neural network and Pattern recognition.
Artificial intelligence connects with themes related to Machine learning in his study.
His biological study focuses on Motion.
His Image quality research is multidisciplinary, incorporating elements of Mean opinion score, Quality assessment, Database and Distortion.
His Artificial neural network study combines topics in areas such as Speech recognition, Quality of experience, Face and Perception.
Guangtao Zhai incorporates Pattern recognition and Distortion in his research.
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