Graph-Based Surveillance is a surveillance methodology that utilizes graph theory and network analysis to model, detect, and analyze anomalous trading behaviors by representing financial entities and their interactions as nodes and edges within a structured graph.
6
Publications
167
Citations
16
Authors
7
Institutions
Publications per year
2017–2026
2
Parents
Publications
6
Graph coloring based surveillance video synopsis
Yi He, Changxin Gao, Nong Sang et al. · Neurocomputing · 2016 · 50 citations
Stochastic Strategies for Autonomous Robotic Surveillance
Janet Grace, John Baillieul · 2006 · 48 citations
1–5 of 6
Authors
16
- TA
1
h-index
- KKKoichi Kobayashi
Japan Advanced Institute of Science and Technology, Japan
1 publications · 12 citations
1
h-index
- CG
1
h-index
- CT
1
h-index
- FB
1
h-index
1–5 of 16
Institutions
7
Boston University
Boston, United States
1 h-index
2 publications
96 citations
Politecnico di Torino
Turin, Italy
1 h-index
1 publications
11 citations
University of California, Riverside
Riverside, United States
1 h-index
1 publications
11 citations
University of California, Santa Barbara
Santa Barbara, United States
1 h-index
1 publications
11 citations
The University of Tokyo
Tokyo, Japan
1 h-index
3 publications
75 citations
Middle East Technical University
Ankara, Türkiye
1 h-index
2 publications
42 citations
Hokkaido University
Sapporo, Japan
1 h-index
3 publications
36 citations
NeoGenomics (United States)
Aliso Viejo, United States
1 publications
14 citations
1–8 of 7
Venues
- Automatica
1 publications · 11 citations
1
h-index
- Neurocomputing
1 publications · 50 citations
1
h-index
- Advanced Robotics
1 publications · 25 citations
1
h-index
- Big Data Research
1 publications · 21 citations
1
h-index
- SICE Journal of Control Measurement and System Integration
1 publications · 12 citations
1
h-index
1–5