What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Xudong Jiang mainly focuses on Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Discriminative model.
His study in Artificial intelligence focuses on Fingerprint, Minutiae, Segmentation, Pattern recognition and Biometrics.
His Fingerprint research incorporates elements of Fingerprint recognition, Data mining and Signal processing.
His Pattern recognition study combines topics in areas such as Feature, Pixel, Contextual image classification, Object and Facial recognition system.
He interconnects Feature, Support vector machine and Dimensionality reduction in the investigation of issues within Feature extraction.
He works mostly in the field of Discriminative model, limiting it down to concerns involving Local binary patterns and, occasionally, Code and Error detection and correction.
His most cited work include:
- Fingerprint minutiae matching based on the local and global structures (454 citations)
- Eigenfeature Regularization and Extraction in Face Recognition (281 citations)
- Context Contrasted Feature and Gated Multi-scale Aggregation for Scene Segmentation (200 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Optoelectronics and Optics.
Feature extraction, Facial recognition system, Pixel, Discriminative model and Face are the primary areas of interest in his Artificial intelligence study.
Xudong Jiang has researched Feature extraction in several fields, including Feature, Biometrics, Linear discriminant analysis, Dimensionality reduction and Discriminant.
His Facial recognition system study incorporates themes from Subspace topology, Machine learning, Sparse approximation and Training set.
His Pattern recognition study also includes
- Feature that intertwine with fields like Feature vector,
- Fingerprint which is related to area like Minutiae.
The concepts of his Optoelectronics study are interwoven with issues in Avalanche photodiode, Photon counting and Avalanche diode.
He most often published in these fields:
- Artificial intelligence (61.96%)
- Pattern recognition (47.83%)
- Computer vision (25.36%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (61.96%)
- Pattern recognition (47.83%)
- Segmentation (7.25%)
In recent papers he was focusing on the following fields of study:
Xudong Jiang focuses on Artificial intelligence, Pattern recognition, Segmentation, Discriminative model and Deep learning.
His research is interdisciplinary, bridging the disciplines of Computer vision and Artificial intelligence.
Xudong Jiang combines subjects such as Leverage and Feature with his study of Pattern recognition.
Xudong Jiang has included themes like Pixel, Convolution and Pascal in his Segmentation study.
The various areas that Xudong Jiang examines in his Discriminative model study include Time domain, Cognitive neuroscience of visual object recognition, Training set and Time–frequency analysis.
His Deep learning research integrates issues from Genetic algorithm, Control reconfiguration and Silicon photonics.
Between 2018 and 2021, his most popular works were:
- Semantic Correlation Promoted Shape-Variant Context for Segmentation (67 citations)
- Boundary-Aware Feature Propagation for Scene Segmentation (64 citations)
- Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features (61 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His main research concerns Artificial intelligence, Pattern recognition, Segmentation, Discriminative model and Convolution.
His research combines Computer vision and Artificial intelligence.
His Pattern recognition study which covers Deep learning that intersects with Pixel.
His Segmentation study combines topics in areas such as Object, Pascal, Feature and Phrase.
His studies deal with areas such as Feature extraction and Training set as well as Discriminative model.
Xudong Jiang combines subjects such as Network architecture and Discriminator with his study of Convolution.
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