What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer vision
Yanwei Pang focuses on Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Linear discriminant analysis.
In his study, Semantics is strongly linked to Machine learning, which falls under the umbrella field of Artificial intelligence.
His Pattern recognition research is multidisciplinary, incorporating elements of Facial recognition system, Image retrieval, Data mining and Cluster analysis.
His Feature extraction study combines topics in areas such as Artificial neural network, Object detection and Feature.
His Computer vision research integrates issues from Distribution and Computation.
The concepts of his Linear discriminant analysis study are interwoven with issues in Image processing, Subspace topology, Algorithm and Dimensionality reduction.
His most cited work include:
- Gabor-Based Region Covariance Matrices for Face Recognition (252 citations)
- Photo2Trip: generating travel routes from geo-tagged photos for trip planning (237 citations)
- L1-Norm-Based 2DPCA (230 citations)
What are the main themes of his work throughout his whole career to date?
Yanwei Pang mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Object detection.
His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning.
Yanwei Pang combines subjects such as Subspace topology and Facial recognition system with his study of Pattern recognition.
In general Computer vision, his work in Image restoration, Image segmentation, Histogram and Filter is often linked to Key linking many areas of study.
His research investigates the link between Feature extraction and topics such as Convolutional neural network that cross with problems in Artificial neural network and Linear filter.
The Principal component analysis study combines topics in areas such as Outlier and Robustness.
He most often published in these fields:
- Artificial intelligence (81.25%)
- Pattern recognition (46.63%)
- Computer vision (26.44%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (81.25%)
- Pattern recognition (46.63%)
- Feature extraction (24.04%)
In recent papers he was focusing on the following fields of study:
Yanwei Pang spends much of his time researching Artificial intelligence, Pattern recognition, Feature extraction, Machine learning and Object detection.
His Artificial intelligence study frequently draws connections between related disciplines such as Computer vision.
His research in the fields of Discriminative model and Similarity overlaps with other disciplines such as Exploit.
Yanwei Pang has included themes like Point cloud, Point and Convolutional neural network in his Feature extraction study.
His studies in Machine learning integrate themes in fields like Thesaurus and Robustness.
His Object detection study combines topics from a wide range of disciplines, such as Face detection and Pyramid.
Between 2019 and 2021, his most popular works were:
- Video Summarization With Attention-Based Encoder–Decoder Networks (76 citations)
- Attribute-Guided Network for Cross-Modal Zero-Shot Hashing (31 citations)
- Attention Scaling for Crowd Counting (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
Yanwei Pang mainly focuses on Artificial intelligence, Pattern recognition, Feature extraction, Object detection and Convolutional neural network.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Scale, Machine learning and Computer vision.
His work on Stereopsis as part of general Computer vision study is frequently linked to Transformation and Visual perception, therefore connecting diverse disciplines of science.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Variation and Pascal.
His studies deal with areas such as Salient and Pyramid as well as Feature extraction.
The various areas that Yanwei Pang examines in his Convolutional neural network study include Artificial neural network, Biometrics, Generalization and Identification.
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