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pro vyhledávání: '"Jakkala, Kalvik"'
Autor:
Jakkala, Kalvik, Akella, Srinivas
Wastewater monitoring is an effective approach for the early detection of viral and bacterial disease outbreaks. It has recently been used to identify the presence of individuals infected with COVID-19. To monitor large communities and accurately loc
Externí odkaz:
http://arxiv.org/abs/2312.16750
Multi-Robot Informative Path Planning from Regression with Sparse Gaussian Processes (with Appendix)
Autor:
Jakkala, Kalvik, Akella, Srinivas
This paper addresses multi-robot informative path planning (IPP) for environmental monitoring. The problem involves determining informative regions in the environment that should be visited by robots to gather the most information about the environme
Externí odkaz:
http://arxiv.org/abs/2309.07050
Autor:
Jakkala, Kalvik, Akella, Srinivas
The sensor placement problem is a common problem that arises when monitoring correlated phenomena, such as temperature, precipitation, and salinity. Existing approaches to this problem typically formulate it as the maximization of information metrics
Externí odkaz:
http://arxiv.org/abs/2303.00028
Autor:
Pinyoanuntapong, Ekkasit, Ali, Ayman, Jakkala, Kalvik, Wang, Pu, Lee, Minwoo, Peng, Qucheng, Chen, Chen, Sun, Zhi
mmWave radar-based gait recognition is a novel user identification method that captures human gait biometrics from mmWave radar return signals. This technology offers privacy protection and is resilient to weather and lighting conditions. However, it
Externí odkaz:
http://arxiv.org/abs/2301.13384
Autor:
Jakkala, Kalvik
Gaussian processes are one of the dominant approaches in Bayesian learning. Although the approach has been applied to numerous problems with great success, it has a few fundamental limitations. Multiple methods in literature have addressed these limi
Externí odkaz:
http://arxiv.org/abs/2106.12135
Gait is a person's natural walking style and a complex biological process that is unique to each person. Recently, the channel state information (CSI) of WiFi devices have been exploited to capture human gait biometrics for user identification. Howev
Externí odkaz:
http://arxiv.org/abs/1902.02300
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