Convolutional neural network (CNN)-based deep learning (DL) is a powerful, recently
developed image classification approach. With origins in the computer vision and image …

In regular convolutional neural networks (CNN), fully-connected layers act as classifiers to
estimate the probabilities for each instance in classification tasks. The accuracy of CNNs can …

Compressive spectral imaging (CSI) has attracted significant attention since it employs
synthetic apertures to codify spatial and spectral information, sensing only 2D projections of …

Hyperspectral imaging (HSI) is a powerful technology already used for many objectives in
agriculture. Applications include disease monitoring, plant phenotyping, yield estimation or …

Over the last decade, a 3D reconstruction technique has been developed to present the
latest as-is information for various objects and build the city information models. Meanwhile …

Multispectral filter array (MSFA)-based imaging is a compact, practical technique for
snapshot spectral image capturing and reconstruction. The imaging and reconstruction …

Hyperspectral (HS) sensors sample reflectance spectrum in very high resolution, which
allows us to examine material properties in very fine details. However, their widespread …

As one of the simplest methods to construct snapshot spectral imagers, multispectral filter
array (MSFA) has been applied to commercial miniatured spectral imagers. While most of …

Imaging multiple wavelength and polarization components is problematic due to the
complexity of equipment and the increase in the number of imaging shots, so imaging using …

Multispectral filter array (MSFA) imaging with one single sensor is a portable and
inexpensive means of acquiring spectral image which is widely used for object detection …