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Muhammad Ismaeel Khan

Datos Biográficos

ID7989017
NOMBREMuhammad Ismaeel Khan
NOMBRESMuhammad Ismaeel
APELLIDOKhan
FIRMAKHAN M I
VERIFICADONo
TOTAL DE OBRAS1
TOTAL DE CITAS0
OBRAS COMO AUTOR1
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2023
AÑO MÁS RECIENTE DE PUBLICACIÓN2023
ÍNDICE H0
  • Anomaly Detection In Ioht Using Deep Learning

    Open Access•Aftab Arif, Fadia Shah et al.•ARTICLE•MIGRATION LETTERS•2023

    Anomaly detection has been a focal point in research within the data mining community, with numerous methods developed over the years. A significant challenge that has emerged in recent years, impacting the practical implementation of [1]these algorithms, is the lack of trust from end-users. This research introduces a novel model that capitalizes on correlations among physiological data attributes, integrating hybrid Convolutional Long Short-Term…

Sin obras prominentes en esta página.

  • Anomaly Detection In Ioht Using Deep Learning

    Open Access•Aftab Arif, Fadia Shah et al.•ARTICLE•MIGRATION LETTERS•2023

    Anomaly detection has been a focal point in research within the data mining community, with numerous methods developed over the years. A significant challenge that has emerged in recent years, impacting the practical implementation of [1]these algorithms, is the lack of trust from end-users. This research introduces a novel model that capitalizes on correlations among physiological data attributes, integrating hybrid Convolutional Long Short-Term…

Advanced Malware Detection Techniques (1 obra) · Anomaly detection (1 obra) · Anomaly Detection Techniques and Applications (1 obra) · Big data (1 obra) · Health care (1 obra) · Health data (1 obra) · Healthcare Technology and Patient Monitoring (1 obra) · Medical device (1 obra) · Point (geometry (1 obra) · Reliability (semiconductor (1 obra)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae