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查看斯高帕斯 (Scopus) 概要
謝 君偉
教授
智慧計算與科技研究所
電話
06-3032121 # 57909
電子郵件
jwhsieh
nctu.edu
tw
網站
https://aicvlab2019.wordpress.com/
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7952
引文
33
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引文
16
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697
引文
12
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1993 …
2026
每年研究成果
概覽
指紋
網路
計畫
(13)
研究成果
(208)
類似的個人檔案
(3)
指紋
查看啟用 Jun-Wei Hsieh 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
Experimental Result
100%
Object Detection
54%
Convolutional Neural Network
31%
Vehicle Detection
28%
Deep Learning Method
27%
Attention (Machine Learning)
26%
Traditional Method
26%
Multiplicity
23%
Lighting Condition
22%
Sparse Representation
20%
Neural Architecture Search
19%
Event Analysis
18%
Video Sequences
16%
Approximation (Algorithm)
16%
Artificial Intelligence
15%
Behavior Analysis
15%
Background Subtraction
14%
Recognition System
14%
Feature Map
13%
Vision Transformer
13%
Feature Fusion
12%
Information Retrieval
12%
Classification Scheme
12%
Recognition Accuracy
12%
Motion Feature
12%
Image Restoration
11%
Annotation
11%
Event Detection
11%
Support Vector Machine
11%
Tracking (Position)
11%
Color Classification
11%
Few-Shot Learning
11%
Color Correction
11%
Image Segmentation
11%
Process Optimization
10%
Detection Accuracy
10%
Time Complexity
10%
Gaussian Mixture Model
10%
Action Sequence
10%
Video Retrieval
10%
Feature Extraction
9%
Captured Image
9%
Training Sample
9%
Adaboost Algorithm
9%
Extracted Feature
9%
Weather Condition
9%
YOLOv3
8%
Residual Neural Network
8%
Speed-up
8%
Template Matching
8%
Keyphrases
Object Detection
32%
Vehicle Detection
30%
Occlusion
22%
Sparse Representation
20%
Lighting Conditions
19%
Lighting Changes
19%
Event Analysis
17%
License Plate
16%
Time Order
16%
Symmelet
16%
Different Lighting
15%
Deep Learning
14%
Pedestrian
14%
Process Optimization
13%
Symmetrical SURF
13%
Road Signs
13%
Triangulation
13%
Histogram
12%
License Plate Recognition
12%
Deformable
12%
Feature Pyramid Network
12%
Cross-attention
12%
Classification Scheme
12%
Moving Object Detection
11%
Vehicle Make Recognition
11%
Vehicle Recognition
11%
Vehicle Classification
11%
Matching Pairs
11%
Neural Architecture Search
11%
Motion Features
11%
Vehicle Color Recognition
11%
Eigen
11%
Few-shot Learning
11%
Color Correction
11%
Helmet
11%
Multiplicity Problem
10%
Recognition System
10%
Video Sequences
10%
Background Subtraction
10%
Morphology-based
10%
Concatenated
10%
Edge-based
10%
Key Posture
9%
Reverse-time
9%
Multi-object Tracking
9%
Partial Networking
9%
Vehicle Colors
9%
Video Retrieval
9%
Wavelet Basis
9%
Multiple Persons
9%
