Efficient Curriculum based Continual Learning with Informative Subset Selection for Remote Sensing Scene Classification

Autor: Bhat, S Divakar, Banerjee, Biplab, Chaudhuri, Subhasis, Bhattacharya, Avik

We tackle the problem of class incremental learning (CIL) in the realm of landcover classification from optical remote sensing (RS) images in this paper. The paradigm of CIL has recently gained much prominence given the fact that data are generally o

Externí odkaz: http://arxiv.org/abs/2309.01050

Long-term accuracy of the National Emergency Laparotomy Audit risk score: Analysis of the impact of comorbidities on mortality 5 years after emergency laparotomy.

Autor: Barazanchi AWH; From the Department of Surgery (A.W.H.B., S.B., B.P., W.M., W.X., A.D.M., A.T., A.G.H.), Faculty of Medical and Health Sciences, The University of Auckland, Auckland; Department of General Surgery (A.W.H.B.), Capital and Coast District Health Board, Wellington; Department of Surgery (S.B.), Te Whatu Ora MidCentral, Palmerston North; Faculty of Health and Environmental Science (I.Z.), School of Clinical Science, Auckland University of Technology; Department of Surgery (A.D.M., A.G.H.), Middlemore Hospital, Te Whatu Ora Counties Manukau; and Department of Surgery (A.T.), Te Toka Tumai Auckland, Auckland, New Zealand., Bhat S, Park B, Zeng I, MacFater W, Xia W, MacCormick AD, Taneja A, Hill AG

Publikováno v: The journal of trauma and acute care surgery [J Trauma Acute Care Surg] 2024 Nov 18. Date of Electronic Publication: 2024 Nov 18.

Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation

Autor: Banerjee, Sayan, Bhat, S Divakar, Chaudhuri, Subhasis, Velmurugan, Rajbabu

In this paper, we propose a novel framework for multi-image co-segmentation using class agnostic meta-learning strategy by generalizing to new classes given only a small number of training samples for each new class. We have developed a novel encoder

Externí odkaz: http://arxiv.org/abs/2010.08800

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Radiation hard DMAPS pixel sensors in 150nm CMOS technology for operation at LHC

Autor: Barbero, M., Barrillon, P., Bespin, C., Bhat, S., Breugnon, P., Caicedo, I., Chen, Z., Degerli, Y., Dingfelder, J., Godiot, S., Guilloux, F., Hemperek, T., Hirono, T., Hügging, F., Krüger, H., Moustakas, K., Ouraou, A., Pangaud, P., Peric, I., Pohl, D-L., Rymaszewski, P., Schwemling, P., Vandenbroucke, M., Wang, T., Wermes, N.

Publikováno v: Journal of Instrumentation, 15 05 (2020) P05013-P05013

Monolithic Active Pixel Sensors (MAPS) have been developed since the late 1990s employing silicon substrate with a thin epitaxial layer in which deposited charge is collected by disordered diffusion rather than by drift in an electric field. As a con

Externí odkaz: http://arxiv.org/abs/1911.01119