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Found 7 papers, 2 papers with code
Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis
The domain of online learning has experienced multifaceted expansion owing to its prevalence in real-life applications.
MiShape: 3D Shape Modelling of Mitochondria in Microscopy
Fluorescence microscopy is a quintessential tool for observing cells and understanding the underlying mechanisms of life-sustaining processes of all living organisms.
Physics-guided Loss Functions Improve Deep Learning Performance in Inverse Scattering
Solving electromagnetic inverse scattering problems (ISPs) is challenging due to the intrinsic nonlinearity, ill-posedness, and expensive computational cost.
Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning
Therefore, noise or artefact models in nanoscopy images cannot be explicitly learned.
Object detection neural network improves Fourier ptychography reconstruction
Intriguingly, we find that conventionally beneficial smoothing and filtering of raw data is counterproductive in this type of application.
Simulation-supervised deep learning for analysing organelles states and behaviour in living cells
Performing artificial intelligence (AI) tasks such as segmentation, tracking, and analytics of small sub-cellular structures such as mitochondria in microscopy videos of living cells is a prime example.
Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
Streaming classification methods assume the number of input features is fixed and always received.
