Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Satarupa Uttarkabat"'
Publikováno v:
Advances in Data Science and Adaptive Analysis. 14
Neighborhood-based unsupervised approaches like LDOF, LOF and symmetric neighborhood (INFLO) have proven effective over decades. These techniques principally utilize the information of either the [Formula: see text]-nearest neighbor or the reverse [F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f0b3024d4a6fcee5fe1c83eec22e484
https://doi.org/10.1142/s2424922x22500115
https://doi.org/10.1142/s2424922x22500115
Publikováno v:
2021 IEEE 18th India Council International Conference (INDICON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1f7cdd9807965fcdbcdbf00ac5ba7b1
https://doi.org/10.1109/indicon52576.2021.9691610
https://doi.org/10.1109/indicon52576.2021.9691610
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811599262
This paper presents a contactless system based on twin channels of thermal and visual image sequences to register the affective states of an individual during Human–Computer Interaction (HCI). The negative affective states such as stress, anxiety,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3cc148eef41066eb035ab56e9ff0bc66
https://doi.org/10.1007/978-981-15-9927-9_7
https://doi.org/10.1007/978-981-15-9927-9_7
Publikováno v:
2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184).
This paper presents a non-contact system based on twin channels of thermal and visual image sequences to register the affective states of an individual during Human-Computer Interaction (HCI). The negative affective states such as stress, anxiety, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7344a4d5598e3cb575f02016b0ead3dc
https://doi.org/10.1109/icoei48184.2020.9142883
https://doi.org/10.1109/icoei48184.2020.9142883
Publikováno v:
2020 4th International Conference on Computational Intelligence and Networks (CINE).
Unsupervised learning techniques are popular in detecting outliers in various domains. Many parametric and non-parametric outlier detection approaches have been proposed over the last decades. The existing neighborhood-based non-parametric unsupervis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d775691f05037b4e481856dbc2fca9a
https://doi.org/10.1109/cine48825.2020.234401
https://doi.org/10.1109/cine48825.2020.234401
Publikováno v:
IEEE Consumer Electronics Magazine. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dcebdbf0ca821b07cb5b7ee7ca2beb8
https://doi.org/10.1109/mce.2022.3153748
https://doi.org/10.1109/mce.2022.3153748