Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Light-Field Microscopy for optical imaging of neuronal activity: when
  model-based methods meet data-driven approaches   Understanding how networks of neurons process information is one of the key
challenges in modern neuroscience. A necessary step to achieve this goal is to
be able to observe the dynamics of large populations of neurons over a large
area of the brain. Light-field microscopy (LFM), a type of scanless microscope,
is a particularly attractive candidate for high-speed three-dimensional (3D)
imaging. It captures volumetric information in a single snapshot, allowing
volumetric imaging at video frame-rates. Specific features of imaging neuronal
activity using LFM call for the development of novel machine learning
approaches that fully exploit priors embedded in physics and optics models.
Signal processing theory and wave-optics theory could play a key role in
filling this gap, and contribute to novel computational methods with enhanced
interpretability and generalization by integrating model-driven and data-driven
approaches. This paper is devoted to a comprehensive survey to state-of-the-art
of computational methods for LFM, with a focus on model-based and data-driven
approaches.

18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
23
The categories of this paper are: solv-int
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an