邵俊明
-
教授
博士生导师
- 性别：男
- 毕业院校：慕尼黑大学
- 学历：博士研究生毕业
- 学位：理学博士学位
- 在职信息：在职人员
- 所在单位：计算机科学与工程学院（网络空间安全学院）
- 电子邮箱：2b7f89429fa274149ace54dc6c06275e42712438220e9bb6a33f754f49ee266820ea2734a3916d4ac9b37d2acda9613706635314be5d8407a486e9e7f6f5bf244e1aa5694929f1b2e740f3c14e92094214bce5679d477a8d0dab240c23a7d70ec8c2ea5155923100f88a854251e6d942eb2157d4bf9752d758e0407cdb2745f2
访问量：
-
[1]
Q :,
Yang,
N,
Gen,
J,
Shao,
D,
and He,
A Model for Image Categorization Based on Biological Visual Mechanism
-
[2]
Q :,
Yang,
D,
He,
J,
and Shao,
Multi-semantic Scene Classification Based on Region of Interest
-
[3]
C.:,
Plant,
C,
Boehm,
C,
Hahn,
A,
Wohlschläger,
J,
and Shao,
Density-based Clustering of White Matter Tracts in the Human Brain with Dynamic Time Warping
-
[4]
C.:,
Plant,
N.,
Myers,
A.,
Wohlschlaeger,
C.,
Boehm,
Q.,
Yang,
K.,
Hahn,
J.,
and Shao,
Combining Time Series Similarity with Density-Based Clustering to Identify Fiber Bundles in the Human Brain
-
[5]
C.:,
Plant,
N.,
Myers,
C.,
Boehm,
A.,
Wohlschlaeger,
Q.,
Yang,
K.,
Hahn,
J.,
and Shao,
Hierarchical Density-based Clustering of White Matter Tracts in the Human Brain
-
[6]
J.:,
Shao,
C.,
Plant,
S. M.,
Mai,
X.,
He,
J.,
Feng,
C.,
and Boehm,
A Novel Similarity Measure for Fiber Clustering using Longest Common Subsequence
-
[7]
C.:,
Plant,
Q.,
Yang,
C.,
Boehm,
J.,
and Shao,
Synchronization Based Outlier Detection
-
[8]
Q.:,
Yang,
J.*,
Shao,
C.,
Plant,
C.,
and Boehm,
Clustering by synchronization
-
[9]
C.:,
Boehm,
C.,
Plant,
J.,
Shao,
K.,
Haegler,
N.S.,
and Mueller,
Weighted Graph Compression for Parameter-free Clustering WithPaCCo
-
[10]
M:,
Scholz,
J,
Shao,
Q,
and Yang,
Classification of Water Bodies including Sustainable Flood Retention Basins (SFRB)
-
[11]
C:,
Plant,
M,
Scholz,
J,
Shao,
Q,
and Yang,
Feature selection methods for characterizing and classifying adaptive Sustainable Flood Retention Basins
-
[12]
J:,
Shao,
M,
Scholz,
Q,
and Yang,
Application of Spatial Statistics as a Screening Tool for Sustainable Flood Retention Basin Management
-
[13]
C.:,
Plant,
C.,
Boehm,
Q.,
Yang,
J.,
and Shao,
Detection of Arbitrarily Oriented Synchronized Clusters in High-dimensional Data
-
[14]
C:,
Boehm,
A,
Meyer-Baese,
F,
Theis,
J,
Shao,
SM,
Thai,
C,
and Plant,
Predicting dam failure risk for sustainable flood retention basins: A generic case study for the wider Greater Manchester area
-
[15]
C:,
Plant,
C,
Boehm,
M,
Scholz,
J,
Shao,
Q,
and Yang,
Multi-label classification model for Sustainable Flood Retention Basins
-
[16]
M:,
Scholz,
J,
Shao,
Q,
and Yang,
Prediction of Sustainable Flood Retention Basin Characteristics using a Self-Organizing Map
-
[17]
C:,
Boehm,
A,
Meyer-Baese,
F,
Theis,
J,
Shao,
SM,
Thai,
C,
and Plant,
Measuring Non-Gaussianity by Phi-transformed and Fuzzy Histograms
-
[18]
Sorg C.:,
Wohlschlaeger A.,
Yang Q.,
and Shao J.,
Discovering Aberrant Patterns of Human Connectome in Alzheimer’s Disease via Subgraph Mining
-
[19]
C.:,
Sorg,
A.,
Wohlschläger,
V.,
Riedl,
C.,
Meng,
C.,
Zimmer,
A.,
Kurz,
H.,
Förstl,
C.,
Böhm,
C.,
Plant,
J.,
Feng,
Q.,
Yang,
N.,
Myers,
J.,
and Shao,
Prediction of Alzheimer’s disease using individual structural connectivity networks
-
[20]
J:
and Shao,
Synchronization on Data Mining
