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WEI KE
Professor
Professor
,
Faculty of Applied Sciences
Phone
8599 6452
Email
wke
mpu.edu
mo
h-index
1840
Citations
24
h-index
Calculated based on number of publications stored in Pure and citations from Scopus
2009
2026
Research activity per year
Overview
Fingerprint
Network
Research Output
(230)
Press/Media
(33)
Similar Profiles
(6)
Fingerprint
Dive into the research topics where WEI KE is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Weight
Alphabetically
Computer Science
Reidentification
100%
Experimental Result
93%
Convolutional Neural Network
86%
Person Re-Identification
76%
Deep Learning Method
66%
Attention (Machine Learning)
64%
fault diagnose method
63%
Tracking (Position)
57%
Fault Diagnosis
55%
Tracking Object
49%
super resolution
48%
Neural Network
47%
local feature
37%
Feature Extraction
33%
Object Detection
31%
Generative Adversarial Networks
30%
Type Systems
28%
data association
27%
Tracking Algorithm
27%
Representation Learning
26%
Dynamic Time Warping
25%
Computer Vision
25%
Image Classification
25%
Graph Convolutional Network
24%
Feature Fusion
24%
Discriminative Feature
24%
Depth Estimation
22%
Motion Model
22%
Requirements Models
22%
Recurrent Neural Network
21%
Classification Accuracy
21%
Software Development
19%
Received Signal Strength
19%
Tracking System
19%
Classification Performance
18%
Activation Function
18%
Learning System
17%
Machine Learning
17%
Model-Driven Engineering
17%
Discriminant Analysis
17%
Temporal Feature
17%
Blockchain
16%
Artificial Intelligence
16%
Fast Convergence
16%
Matching Model
15%
Privacy Protection
15%
Text Classification
15%
Object Detector
15%
Appearance Model
15%
introductory programming course
15%
Engineering
Fault Diagnosis
45%
Deep Learning Method
41%
Light Field
38%
Convolutional Neural Network
38%
Multiscale
25%
Feature Extraction
23%
Received Signal Strength
19%
Recurrent
15%
Rigid Structure
15%
Positioning Algorithm
15%
Nearest Neighbor
15%
Image Classification
15%
Experimental Result
14%
Field Image
11%
Tracking Algorithm
11%
Limitations
11%
Additional Training
11%
Classification Performance
11%
Similarities
11%
Energy Engineering
10%
Compression Factor
9%
Level Feature
9%
Morphological Filter
9%
Rank Order
9%
Metrics
9%
Learning System
8%
Collected Data
8%
State-of-the-Art Method
7%
Deformable Body
7%
Activation Function
7%
Multi--Target Tracking
7%
Matching Model
7%
Motion Model
7%
Instantiation
7%
Massive MIMO
7%
Image Coding
7%
Angular Correlation
7%
Adjacent Frame
7%
Partial Occlusion
7%
Nearby Object
7%
Detection Algorithm
7%
Multistage
7%
Critical Application
7%
Frequency Part
7%
Synthesis Method
7%
Polynomial Time
7%
Medical Image
7%
Compression Ratio
7%
Scale Cross
7%
Allocation
7%
