Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Sundip R. Desai"'
Autor:
Sriram Baireddy, Sundip R. Desai, Richard H. Foster, Moses W. Chan, Mary L. Comer, Edward J. Delp
Publikováno v:
2023 IEEE Aerospace Conference.
Autor:
Sriram Baireddy, Moses W. Chan, Sundip R. Desai, Richard H. Foster, Mary L. Comer, Edward J. Delp
Publikováno v:
2022 IEEE Aerospace Conference (AERO).
Publikováno v:
2022 IEEE Aerospace Conference (AERO).
Autor:
Mary L. Comer, Edward J. Delp, James L. Mathieson, Sundip R. Desai, Moses W. Chan, Sriram Baireddy, Richard H. Foster
Publikováno v:
CVPR Workshops
Anomaly detection in telemetry channels is a high priority for spacecraft, especially when considering the harsh environment of space and the magnitude of launch and operation costs. Traditional spacecraft anomaly detection methods are limited in sco
Autor:
Moses W. Chan, Shabab Siddiq, Nhat X. Nguyen, Sundip R. Desai, Timothy Overman, Krystle Beaulieu, Lawrence Schirmer
Publikováno v:
Automatic Target Recognition XXXI.
Autor:
Moses W. Chan, Sundip R. Desai, James L. Mathieson, Tianyu Li, Mary L. Comer, Edward J. Delp, Richard H. Foster
Publikováno v:
2020 IEEE Aerospace Conference.
Prediction-based anomaly detection methods for time series have been studied for decades and demonstrated to be useful in many applications. However, many predictors cannot accurately predict values around abrupt changes in time series, which may res
Autor:
Tianyu Li, Richard H. Foster, Moses W. Chan, Edward J. Delp, Sundip R. Desai, Mary L. Comer, James L. Mathieson
Publikováno v:
MILCOM
Anomaly or abnormal behavior detection in downlinked spacecraft telemetry is a key step for determining root cause of subsystem failures. Long Short-Term Memory networks (LSTMs) have been demonstrated to be useful for anomaly detection in time series
Publikováno v:
Automatic Target Recognition XXIX.