INSTITUTIONAL DIGITAL REPOSITORY

Browsing by Author "Bagchi, S."

Browsing by Author "Bagchi, S."

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  • Adequately wide 1D CNN facilitates improved EEG based visual object recognition 
    Bagchi, S.; Bathula, D.R. (2022-09-03)
    Accurate classification of visual objects from Single-Trial EEG signals is a challenging task due to the low signal-to-noise ratio (SNR) associated with the brain signals. Recently, machine learning frameworks based on ...
  • EEG-ConvTransformer for single-trial EEG-based visual stimulus classification 
    Bagchi, S.; Bathula, D.R. (2022-07-17)
    Different categories of visual stimuli evoke distinct activation patterns in the human brain. These patterns can be captured with EEG for utilization in application such as Brain-Computer Interface (BCI). However, accurate ...
  • Learning a Meta-Ensemble technique for skin lesion classification and novel class detection 
    Bagchi, S.; Banerjee, A.; Bathula, D. R. (2021-06-24)
    The frequency and fatality rates associated with skin Melanoma requires an accurate and efficient detection methodology to enable early medical diagnosis. Artificial Intelligence (AI) augmented detection methods aim ...
  • Nature of seniority symmetry breaking in the semimagic nucleus Ru 94 
    Das, B.; Cederwall, B.; Qi, C.; Górska, M.; Regan, P.H.; Aktas, Ö.; Albers, H.M.; Banerjee, A.; Chishti, M.M.R.; Gerl, J.; Hubbard, N.; Jazrawi, S.; Sharma, A.; Jolie, J.; Mistry, A.K.; Polettini, M.; Yaneva, A.; Alhomaidhi, S.; Zhao, J.; Arici, T.; Bagchi, S.; Benzoni, G.; Boutachkov, P.; Davinson, T.; T. Dickel, T.; Haettner, E.; Hal, O.; Hornung, Ch.; Hucka, J.P.; John, P.R. (2022-06-22)
    Direct lifetime measurements via γ-γ coincidences using a fast timing detector array consisting of LaBr3(Ce) scintillators has been applied to determine the lifetime of low-lying states in the semimagic (N=50) nucleus Ru94. ...