What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Artificial intelligence, Pattern recognition, Mathematical optimization, Algorithm and Computer vision are his primary areas of study.
In his study, Community structure is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence.
The Mathematical optimization study combines topics in areas such as Convergence and Benchmark.
Licheng Jiao works mostly in the field of Cluster analysis, limiting it down to topics relating to Data mining and, in certain cases, Complex network, as a part of the same area of interest.
As a part of the same scientific family, Licheng Jiao mostly works in the field of Feature extraction, focusing on Artificial neural network and, on occasion, Backstepping and Control theory.
His studies in Evolutionary algorithm integrate themes in fields like Evolutionary computation, Optimization problem, Artificial immune system and Selection.
His most cited work include:
- Wavelet support vector machine (390 citations)
- A novel genetic algorithm based on immunity (381 citations)
- Multiobjective immune algorithm with nondominated neighbor-based selection (343 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Algorithm and Cluster analysis.
His study in Synthetic aperture radar, Feature extraction, Contextual image classification, Hyperspectral imaging and Image falls under the purview of Artificial intelligence.
Licheng Jiao usually deals with Feature extraction and limits it to topics linked to Deep learning and Convolutional neural network.
Licheng Jiao has researched Pattern recognition in several fields, including Pixel and Feature.
His Algorithm study combines topics from a wide range of disciplines, such as Artificial immune system and Mathematical optimization.
His Mathematical optimization research is multidisciplinary, incorporating elements of Convergence, Selection and Benchmark.
He most often published in these fields:
- Artificial intelligence (67.56%)
- Pattern recognition (46.70%)
- Computer vision (20.42%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (67.56%)
- Pattern recognition (46.70%)
- Feature extraction (11.28%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Pattern recognition, Feature extraction, Contextual image classification and Convolutional neural network.
His works in Hyperspectral imaging, Deep learning, Synthetic aperture radar, Pixel and Image are all subjects of inquiry into Artificial intelligence.
His Synthetic aperture radar study combines topics in areas such as Image processing and Speckle pattern.
Licheng Jiao works mostly in the field of Pattern recognition, limiting it down to concerns involving Cluster analysis and, occasionally, Fuzzy logic.
His research investigates the connection with Feature extraction and areas like Remote sensing which intersect with concerns in Object detection.
The various areas that Licheng Jiao examines in his Convolutional neural network study include Artificial neural network and Convolution.
Between 2017 and 2021, his most popular works were:
- A Survey of Deep Learning-Based Object Detection (154 citations)
- A deep learning framework for remote sensing image registration (77 citations)
- Non-Negative Spectral Learning and Sparse Regression-Based Dual-Graph Regularized Feature Selection (53 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Licheng Jiao mainly investigates Artificial intelligence, Pattern recognition, Feature extraction, Convolutional neural network and Deep learning.
Artificial intelligence is represented through his Hyperspectral imaging, Pixel, Contextual image classification, Artificial neural network and Cluster analysis research.
Licheng Jiao has included themes like Synthetic aperture radar, Change detection and Spatial analysis in his Pattern recognition study.
His Synthetic aperture radar research is included under the broader classification of Computer vision.
His Feature extraction research also works with subjects such as
- Remote sensing which connect with Iterative reconstruction and Transfer of learning,
- Robustness which is related to area like Machine learning.
His Deep learning study deals with Benchmark intersecting with Particle swarm optimization and Optimization problem.
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