What is he best known for?
The fields of study Jianfei Cai is best known for:
- Data compression
- Computer vision
- Rate–distortion optimization
His work on Artificial intelligence as part of general Convolutional neural network study is frequently linked to Pattern recognition (psychology), bridging the gap between disciplines.
His work on Artificial intelligence is being expanded to include thematically relevant topics such as Object (grammar).
In his works, he performs multidisciplinary study on Computer vision and Machine learning.
He merges many fields, such as Machine learning and Computer vision, in his writings.
Jianfei Cai connects Algorithm with Computer graphics (images) in his study.
In his papers, he integrates diverse fields, such as Computer graphics (images) and Algorithm.
Segmentation is frequently linked to Image segmentation in his study.
His research is interdisciplinary, bridging the disciplines of Segmentation and Image segmentation.
His research on Mathematical analysis frequently links to adjacent areas such as Boundary (topology).
His most cited work include:
- Recent advances in convolutional neural networks (2432 citations)
- Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding (337 citations)
- A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design (223 citations)
What are the main themes of his work throughout his whole career to date
Artificial intelligence is often connected to Segmentation in his work.
His Computer vision study frequently links to adjacent areas such as Image (mathematics).
His research links Computer vision with Image (mathematics).
He integrates many fields in his works, including Algorithm and Artificial intelligence.
He integrates Computer network with Telecommunications in his study.
He brings together Telecommunications and Computer network to produce work in his papers.
His study brings together the fields of Geodesy and Benchmark (surveying).
Jianfei Cai regularly links together related areas like Benchmark (surveying) in his Geodesy studies.
Jianfei Cai most often published in these fields:
- Artificial intelligence (78.63%)
- Pattern recognition (psychology) (41.22%)
- Computer vision (40.46%)
What were the highlights of his more recent work (between 2020-2022)?
- Artificial intelligence (100.00%)
- Pattern recognition (psychology) (69.23%)
- Machine learning (61.54%)
In recent works Jianfei Cai was focusing on the following fields of study:
In his study, which falls under the umbrella issue of Source code, Encoder, Process (computing), Path (computing) and Pipeline (software) is strongly linked to Operating system.
He conducts interdisciplinary study in the fields of Process (computing) and Operating system through his research.
His work on Path (computing) is being expanded to include thematically relevant topics such as Programming language.
Many of his studies involve connections with topics such as Pipeline (software) and Programming language.
As part of his studies on Artificial intelligence, he often connects relevant areas like Consistency (knowledge bases).
His Pattern recognition (psychology) study often links to related topics such as Facial recognition system.
His Facial recognition system study frequently draws connections between related disciplines such as Pattern recognition (psychology).
His research is interdisciplinary, bridging the disciplines of Leverage (statistics) and Machine learning.
Jianfei Cai frequently studies issues relating to Monocular and Computer vision.
Between 2020 and 2022, his most popular works were:
- 3D Hand Pose Estimation Using Synthetic Data and Weakly Labeled RGB Images (23 citations)
- Semi-supervised Left Atrium Segmentation with Mutual Consistency Training (20 citations)
- Scalable Visual Transformers with Hierarchical Pooling (17 citations)
In his most recent research, the most cited works focused on:
His Machine learning research is intertwined with Leverage (statistics), Discriminative model and Convolutional neural network.
He conducted interdisciplinary study in his works that combined Convolutional neural network and Machine learning.
Computer vision connects with themes related to Monocular, RGB color model and Pose in his study.
His RGB color model study often links to related topics such as Computer vision.
His Pattern recognition (psychology) study frequently draws parallels with other fields, such as Artificial intelligence.
Jianfei Cai combines topics linked to Subspace topology with his work on Artificial intelligence.
While working in this field, Jianfei Cai studies both Quantum mechanics and Entropy (arrow of time).
While working in this field, Jianfei Cai studies both Entropy (arrow of time) and Quantum mechanics.
His research on Operating system frequently links to adjacent areas such as Encoder.
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