What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Geometry
His primary areas of investigation include Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Mathematical optimization.
Artificial intelligence connects with themes related to Iterative method in his study.
His study looks at the relationship between Computer vision and topics such as Interpolation, which overlap with Bilinear interpolation.
His biological study spans a wide range of topics, including Spline, Linear system, Feature and Solid modeling.
His studies deal with areas such as Non-local means, Additive white Gaussian noise, Noise reduction and Cluster analysis as well as Pattern recognition.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Basis, Isogeometric analysis, Matrix norm and Compressed sensing.
His most cited work include:
- New edge-directed interpolation (1766 citations)
- Nonlocally Centralized Sparse Representation for Image Restoration (991 citations)
- Contour-based object tracking with occlusion handling in video acquired using mobile cameras (454 citations)
What are the main themes of his work throughout his whole career to date?
Xin Li mainly investigates Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Optoelectronics.
His work on Machine learning expands to the thematically related Artificial intelligence.
His Computer vision study is mostly concerned with Superresolution, Segmentation, Iterative reconstruction, Motion estimation and Image processing.
Xin Li has included themes like Spline and Mathematical optimization in his Algorithm study.
His Optoelectronics study frequently draws parallels with other fields, such as Optics.
His research in Optics is mostly focused on Grating.
He most often published in these fields:
- Artificial intelligence (42.04%)
- Computer vision (25.04%)
- Algorithm (15.38%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (42.04%)
- Computer vision (25.04%)
- Pattern recognition (15.03%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Deep learning and Feature.
Artificial intelligence is closely attributed to Machine learning in his research.
His studies link Network planning and design with Computer vision.
Xin Li works in the field of Pattern recognition, namely Feature extraction.
His Deep learning research is multidisciplinary, incorporating elements of Noise reduction, Leverage and Iterative reconstruction.
His work is dedicated to discovering how Feature, Pipeline are connected with Benchmark and other disciplines.
Between 2018 and 2021, his most popular works were:
- Constructing efficient mixed-ion perovskite solar cells based on TiO2 nanorod array. (52 citations)
- High‐Performance Perovskite Solar Cells with Enhanced Environmental Stability Based on a (p‐FC6H4C2H4NH3)2[PbI4] Capping Layer (47 citations)
- LO-Net: Deep Real-Time Lidar Odometry (45 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Geometry
The scientist’s investigation covers issues in Artificial intelligence, Perovskite, Computer vision, Deep learning and Pattern recognition.
The various areas that he examines in his Artificial intelligence study include Stability and Pipeline.
His Perovskite research incorporates themes from Layer, Passivation, Optoelectronics and Photovoltaic system.
His work carried out in the field of Computer vision brings together such families of science as Focus, Video quality and Fidelity.
The Deep learning study which covers Noise reduction that intersects with Computer engineering, Regularization, Interpretability, Image restoration and Iterative reconstruction.
His research integrates issues of Background subtraction and Robustness in his study of Pattern recognition.
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