Detection, classification, and tracking of targets

By Dan Li, Kerry D. Wong, Y. Hu, Akbar M. Sayeed. IEEE Signal Processing Magazine, 2002

1,043 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/1f7c4f33425e6aea913d4b00b3d9723d9ee67ea0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Nei Kato
2. Fengxiao Tang
3. Bomin Mao
4. Zubair Muhammad Fadlullah
5. Ali H. Sayed
6. Ali Jadbabaie
7. Shahin Shahrampour
8. Xiuzhen Cheng

In Computer Networks and Communications

1. Ali H. Sayed
2. Nei Kato
3. Fengxiao Tang
4. Bomin Mao
5. Zubair Muhammad Fadlullah
6. G. Sukhatme
7. Andrew Howard
8. Lynne E. Parker

In Electrical and Electronic Engineering

1. Ali H. Sayed
2. A. Hero
3. Doron Blatt
4. G. Sukhatme
5. Andrew Howard
6. Guoliang Xue
7. John Lygeros
8. Stamatis Manesis

Citations in the corpus

• Integrated coverage and connectivity configuration for energy conservation in sensor networks (2005, methodology): “For example, distributed detection based on data fusion [Varshney 1996] requires that every location be monitored by multiple nodes, and distributed tracking and classification [Li et al. 2002] requires even higher degrees of coverage.”
• Vehicle classification in distributed sensor networks (2004, background): “Therefore, efficient collaborative signal processing algorithms that consume less energy for computation and communication are needed for these applications [7].”
• State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems (2017, methodology): “Naturally, the unsupervised ML algorithms have been widely adopted for clustering of WSN nodes and data aggregation problems [149]–[155].”
• Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks (2005, background): “algorithms that consume less energy for computation and less bandwidth for communication are needed [ 3 ].”
• Efficient network flooding and time synchronization with Glossy (2011, methodology): “In surveillance systems, for example, a node detecting an event needs to quickly wake up all other nodes to initiate group formation and collaborative signal processing [ 20 ].”
• Distributed Online Optimization in Dynamic Environments Using Mirror Descent (2016, background): “Classical problems such as decentralized tracking, estimation, and detection are in essence optimization problems [1]–[5].”
• Incremental Adaptive Strategies Over Distributed Networks (2007, background): “Another application of distributed processing is monitoring a moving target in a region monitored by a collection of sensors [ 8 ].”
• Energy-based sensor network source localization via projection onto convex sets (2005, background): “Following [1, 2, 3], the reading of the source’s signal strength at sensor l is modeled by”
• Distributed top-k monitoring (2003, background): “For example, consider the important problem of monitoring computer networks to detect distributed denial-of-service (DDoS) attacks.”