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Wang Qi
Professor
School of Artificial Intelligence, OPtics and Electronics
h-index
13186
Citations
60
h-index
Calculated based on number of publications stored in Pure and citations from Scopus
2009
2025
Research activity per year
Overview
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Network
Research output
(301)
Similar Profiles
(12)
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Dive into the research topics where Qi Wang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Computer Science
Annotation
24%
Anomaly Detection
29%
Art Performance
12%
Attention (Machine Learning)
25%
Band Selection
33%
Clustered Data
13%
Clustering Method
16%
Computer Vision
25%
Convolutional Neural Network
59%
Deep Learning Method
51%
Detection Accuracy
20%
Detection Method
12%
Detection Performance
28%
Detection Result
13%
Dimensionality Reduction
24%
Discriminant Analysis
15%
Discriminative Feature
17%
Domain Adaptation
18%
Experimental Result
96%
Feature Extraction
35%
Feature Fusion
20%
Feature Selection
12%
Fully Convolutional Network
13%
Hyperspectral Image
94%
Image Captioning
23%
Image Classification
22%
Image Segmentation
23%
Linear Discriminant Analysis
16%
local feature
17%
Matrix Factorization
19%
Neural Network
23%
Object Detection
43%
Objective Function
13%
Optical Tracking
13%
Person Re-Identification
16%
Regularization
12%
Remote Sensing Image
100%
remote sensing imagery
19%
Representation Learning
26%
Road Detection
13%
Semantic Feature
14%
Semisupervised Learning
11%
Similarity Graph
13%
Sparse Representation
14%
Spatial Information
13%
super resolution
38%
Superior Performance
13%
Synthetic Data
19%
Unified Framework
13%
Video Sequences
14%
Engineering
Anomaly Detection
13%
Aspect Ratio
8%
Based Segmentation Method
6%
Camera Parameter
6%
Computational Complexity
7%
Computervision
15%
Convolutional Neural Network
19%
Data Point
8%
Deep Learning Method
18%
Detection Algorithm
5%
Detection Performance
5%
Dimensionality
14%
Experimental Result
46%
Extractor
7%
Feature Extraction
9%
Final Result
8%
Gaussians
5%
Geometric Feature
6%
High Resolution
6%
Hyperspectral Data
6%
Hyperspectral Image
65%
Illustrates
5%
Image Classification
11%
Image Data
7%
Image Fusion
6%
Image Synthesis
6%
Joints (Structural Components)
6%
Level Feature
8%
Limitations
6%
Matrix Factorization
6%
Motion Blur
6%
Multiscale
34%
Multispectral Image
6%
Objective Function
8%
Optimal Band
8%
Pixel Level
11%
Real Scene
6%
Road
12%
Road Detection
9%
Scale Variation
11%
Selection Method
11%
Sensing Imagery
11%
Similarity
15%
Sparsity
12%
Spatial Information
5%
State-of-the-Art Method
13%
Truncation
6%
