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查看 Scopus 资料
范 敬凡
光电学院
h-index
1761
引用
21
H-指数
根据储存在 Pure 的刊物以及来自 Scopus 的引用文献数量计算
2010
2025
每年的科研成果
概览
指纹图谱
合作网络
科研成果
(144)
相似学者
(10)
指纹图谱
深入其中 Jingfan Fan 为活跃的研究主题。这些主题标签来自此人的成果。它们共同形成唯一的指纹。
分类
加权
按字母排序
Computer Science
Adversarial Machine Learning
18%
Annotation
10%
Augmented Reality
35%
Automatic Segmentation
23%
Clinical Data
13%
Contextual Information
11%
Convolutional Network
31%
Convolutional Neural Network
19%
de-noising
18%
Deep Learning
28%
Deep Learning Method
16%
Deformation Field
15%
Discriminator
13%
Experimental Result
100%
feature descriptor
14%
Gaussian Mixture Model
10%
Generative Adversarial Networks
14%
Image Analysis
12%
image denoising
11%
Image Sequence
41%
Learning Framework
18%
Lesion Segmentation
21%
Local Structure
14%
maximum-likelihood
14%
Mean Algorithm
14%
Optical Tracking
11%
Point Cloud
44%
Point Sampling
14%
Pose Estimation
18%
Pose Variation
14%
Recurrent Network
14%
Registration Error
17%
Regularization
21%
Rigid Transformation
17%
Segmentation Method
29%
Siamese Neural Network
14%
Structural Similarity
14%
Temporal Feature
17%
Tracking Error
18%
Tracking Object
10%
Tracking System
18%
Traditional Method
10%
Transfer Learning
11%
Transformation Parameter
11%
Tumor Segmentation
14%
U-Net
14%
Ultrasound Image
45%
Vessel Centerline
23%
Vessel Segmentation
31%
Virtual Reality
14%
Engineering
Augmented Reality
23%
Biomechanical Model
14%
Brain Image
9%
Centerline
36%
Component Analysis
8%
Convolutional Neural Network
17%
Coordinate System
15%
Deep Learning
29%
Deep Learning Method
7%
Deformation Field
23%
Demonstrates
52%
Distance Map
8%
Energy Engineering
14%
Error Distance
13%
Experimental Result
56%
Fiducials
12%
Filtration
8%
Gaussian Mixture Model
10%
Gaussians
14%
Geometric Feature
8%
Ground Truth
8%
Guidewire
10%
Imaging Systems
9%
Instrument Calibration
13%
Local Mean
14%
Loss Function
14%
Medical Image
16%
Medical Image Segmentation
8%
Metrics
13%
Multiscale
30%
Navigation System
23%
Network Model
10%
Noise Ratio
8%
Obtains
23%
Optical Axis
8%
Phase Image
7%
Point Cloud
30%
Prediction Performance
8%
Principal Components
8%
Region of Interest
10%
Registration Accuracy
8%
Registration Method
47%
Rigid Transformation
15%
Segmentation Method
15%
Set Point
21%
Side Branch
10%
Similarities
18%
State-of-the-Art Method
45%
Tasks
34%
Transfer Learning
17%
