What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Iris recognition.
Artificial intelligence is closely attributed to Data mining in his research.
His research in Computer vision intersects with topics in Iris and Word error rate.
The various areas that he examines in his Feature extraction study include Feature, Pixel, Contextual image classification, Dimensionality reduction and Discriminative model.
His Iris recognition research is multidisciplinary, incorporating perspectives in IRIS, Segmentation, Iris flower data set and Codebook.
His Facial recognition system research includes themes of Embedding, Convolution, Representation and Subspace topology.
His most cited work include:
- A Light CNN for Deep Face Representation With Noisy Labels (505 citations)
- Ordinal palmprint represention for personal identification [represention read representation] (367 citations)
- Toward Accurate and Fast Iris Segmentation for Iris Biometrics (304 citations)
What are the main themes of his work throughout his whole career to date?
Zhenan Sun spends much of his time researching Artificial intelligence, Pattern recognition, Computer vision, Iris recognition and Facial recognition system.
Feature extraction, Biometrics, Face, Iris and Feature are among the areas of Artificial intelligence where he concentrates his study.
In Feature extraction, Zhenan Sun works on issues like Feature, which are connected to Feature selection.
His Pattern recognition research is multidisciplinary, incorporating elements of Image and Robustness.
His Iris recognition research focuses on IRIS and how it connects with Mobile device.
His biological study spans a wide range of topics, including Classifier, Embedding, Machine learning and Pattern recognition.
He most often published in these fields:
- Artificial intelligence (93.45%)
- Pattern recognition (58.62%)
- Computer vision (47.93%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (93.45%)
- Pattern recognition (58.62%)
- Computer vision (47.93%)
In recent papers he was focusing on the following fields of study:
Zhenan Sun mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Face and Facial recognition system.
His work on Image, Biometrics and Feature as part of general Artificial intelligence research is frequently linked to Focus, thereby connecting diverse disciplines of science.
His work deals with themes such as Margin, Subspace topology and Regression, which intersect with Pattern recognition.
His research ties Iris and Computer vision together.
Zhenan Sun works mostly in the field of Face, limiting it down to topics relating to Inpainting and, in certain cases, Flexibility and Sketch, as a part of the same area of interest.
The concepts of his Facial recognition system study are interwoven with issues in Constraint, Field, Image warping and Pattern recognition.
Between 2018 and 2021, his most popular works were:
- Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition (102 citations)
- A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications (77 citations)
- Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks (48 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Artificial intelligence, Pattern recognition, Facial recognition system, Face and Computer vision are his primary areas of study.
His work on Matching expands to the thematically related Artificial intelligence.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Subspace topology, Compact space, Feature, Leverage and Representation.
His Facial recognition system study combines topics from a wide range of disciplines, such as Centroid, Matching, Constraint, Convolutional neural network and Pattern recognition.
His Face research is multidisciplinary, relying on both Field, Wavelet and Image warping.
His work carried out in the field of Ground truth brings together such families of science as Image resolution, Ranking and Biometrics.
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