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查看斯高帕斯 (Scopus) 概要
鄧 樹傑
Associate Professor
Associate Professor
,
Faculty of Applied Sciences
電話
8599 6491
電子郵件
sktang
mpu.edu
mo
h-index
359
引文
11
h-指數
按照存儲在普爾（Pure）的出版物數量及斯高帕斯（Scopus）引文計算。
2005
2025
每年研究成果
概覽
指紋
網路
研究成果
(75)
新聞/媒體
(15)
類似的個人檔案
(6)
指紋
查看啟用 SU KIT TANG 的研究主題。這些主題標籤來自此人的作品。共同形成了獨特的指紋。
排序方式
重量
按字母排序
Computer Science
Blockchain
96%
Machine Learning
70%
Few-Shot Learning
66%
Internet-Of-Things
63%
Learning System
56%
Deep Learning Method
54%
Convolutional Neural Network
51%
Machine Translation
50%
Case Study
45%
Machine Learning Algorithm
43%
Denial-of-Service Attack
41%
Translation System
36%
Malware
36%
Network Performance
33%
Teaching and Learning
33%
Visible-Infrared Person Re-Identification
33%
Address Configuration
33%
Edge Server
33%
Internet of Things Device
33%
Recurrent Neural Network
33%
User Experience
30%
Machine Learning Technology
27%
Long Short-Term Memory Network
25%
Mobile Internet
25%
Data Augmentation
23%
Prediction Accuracy
23%
Digital Twin
22%
Smart City
22%
Information Storage
22%
Learning Approach
20%
Robot
20%
Computer Vision
19%
On-Line Education
19%
Random Decision Forest
19%
Neighbor Discovery
18%
Internet Infrastructure
16%
Network Partition
16%
Create Network
16%
Network Congestion
16%
Extension Header
16%
Root Mean Squared Error
16%
Experimental Result
16%
Parallel Corpus
16%
Network Protocols
16%
Cloud Storage
16%
Address Autoconfiguration
16%
Synthetic Data
16%
wireless link
16%
Positive Effect
16%
Consortium Blockchain
16%
Engineering
Deep Learning Method
100%
State of Health
45%
Air Quality
38%
Internet-Of-Things
38%
Battery Electric Vehicle
37%
Learning System
37%
Machine Learning Algorithm
33%
Lithium-Ion Batteries
29%
Electric Vehicle
27%
Internet of Things Device
22%
Gaussians
20%
Learning Approach
20%
Filtration
20%
Blockchain
20%
Bridging
16%
Lithium Ion Battery
16%
Distance Estimation
16%
Point Cloud
16%
Adaptive Sensing
16%
Historic Building
16%
Mobile Node
16%
Cooperative
16%
Ideal Solution
16%
Complex Model
16%
Physical Method
16%
Energy Engineering
16%
Bit Error Rate
16%
Decoding Algorithm
16%
Code Book
16%
Reinforcement Learning
16%
Frequency Domain
16%
Practical Significance
16%
State of Charge
16%
End Microcontrollers
16%
Tracking Algorithm
16%
Convolutional Neural Network
16%
Nonlinearity
16%
Experimental Result
15%
Nodes
11%
Computervision
11%
Sensor Device
11%
Frequency Representation
11%
Learning Technique
11%
Spatial Domain
11%
Collected Data
9%
Battery Pack
8%
Memory Requirement
8%
Performance Loss
8%
Storage Capacity
8%
Active Area
8%
