Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Prabhu Janakaraj"'
Autor:
Prabhu Janakaraj, Sriram Boppana, Austars Raymond Schnore, Yang Zhao, Guy Ben-Yosef, Guangliang Zhao, Jianwei Qiu
Publikováno v:
SenSys
Person Re-ID is a challenging problem and is gaining more attention due to demands in security, intelligent system and other applications. Most person Re-ID works are vision-based, such as image, video, or broadly speaking, face recognition-based tec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1c504dca43e53fa1ce039876d692337
https://doi.org/10.1145/3485730.3494113
https://doi.org/10.1145/3485730.3494113
Autor:
Yang Zhao, Prabhu Janakaraj, Lynn Ann DeRose, Gangliang Zhao, Sm Shajed Hasan, Austars Raymond Schnore
Publikováno v:
5GWF
Asset and personnel visibility is crucial for improving workflow efficiency and reducing waste in smart facility, e.g., warehouse applications. 5G networks and technologies provide the high bandwidth and low latency necessary for communicating and fu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f07849661050b216f8673f40f4f820b
https://doi.org/10.1109/5gwf52925.2021.00041
https://doi.org/10.1109/5gwf52925.2021.00041
Autor:
Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang
Federated learning (FL) is a distributed machine learning technology for next-generation AI systems that allows a number of workers, i.e., edge devices, collaboratively learn a shared global model while keeping their data locally to prevent privacy l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26cad363d84b149195b69d8399cafe95
Publikováno v:
INFOCOM Workshops
Self-driving network is an emerging network automation design principle for building next generation autonomous networked systems based on machine learning algorithms trained on real-time experiences, i.e., network state measurements. However, existi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1566457443da2f74975d1d8fcac073fb
https://doi.org/10.1109/infocomwkshps50562.2020.9162923
https://doi.org/10.1109/infocomwkshps50562.2020.9162923
Publikováno v:
SPAWC
Federated learning (FL) has emerged as a key technology for enabling next-generation AI at scale. The classical FL systems use single-hop cellular links to deliver the local models from mobile workers to edge routers that then reach the remote cloud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31b48669e501f5f64d169bca3fbca5f0
https://doi.org/10.1109/spawc48557.2020.9154266
https://doi.org/10.1109/spawc48557.2020.9154266
Publikováno v:
WMNC
Gait is the human’s natural walking style that is a complex biological process unique to each person. This paper aims to exploit millimeter wave (mmWave) to extract fine-grained microdoppler signatures of human movements, which are used as the mmWa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::299ebef1652bdf46de07e806dab91a96
https://doi.org/10.23919/wmnc.2019.8881354
https://doi.org/10.23919/wmnc.2019.8881354
Publikováno v:
Ad Hoc Networks. 105:102163
Recent spectrum measurements show that geo-location spectrum databases are inaccurate in Metropolitan areas by missing a large number of TV white spaces (TVWS). To counter this challenge, this paper introduces a crowd-augmented spectrum database, who
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::099cbbdbb001fad1fd45db11b48fe72d
https://doi.org/10.1016/j.adhoc.2020.102163
https://doi.org/10.1016/j.adhoc.2020.102163
Publikováno v:
ICCCN
Recently, large-scale spectrum measurements show that geo-location spectrum databases, as recommended by regulators (e.g., FCC, Ofcom, ECC) for TV white space (TVWS) discovery are notoriously inaccurate in Metropolitan areas because of inaccurate TV
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32acd7ad7814e26b09ffa5307a5d3f42
https://doi.org/10.1109/icccn.2016.7568586
https://doi.org/10.1109/icccn.2016.7568586