Progress in computing capabilities has enhanced science in many ways. In recent years,
various branches of machine learning have been the key facilitators in forging new paths …

Cloud detection algorithms are crucial in many remote-sensing applications to allow an
optimized processing of the acquired data, without the interference of the cloud fields above …

Deep learning has established many new state of the art solutions in the last decade in
areas such as object, scene and speech recognition. In particular Convolutional Neural …

In this survey, we present a review of methods and resources for texture recognition,
presenting the most common techniques that have been used in the recent decades, along …

Extracting effective features is always a challenging problem for texture classification
because of the uncertainty of scales and the clutter of textural patterns. For texture …

In this paper, a local spatiotemporal descriptor, namely, the volume local binary count
(VLBC), is proposed for the representation and recognition of dynamic texture. This …

Forest species recognition has been traditionally addressed as a texture classification
problem, and explored using standard texture methods such as Local Binary Patterns (LBP) …

When a user scratches a hand-held rigid tool across an object surface, an acceleration
signal can be captured, which carries relevant information about the surface material …

Face recognition remains a challenging problem till today. The main challenge is how to
improve the recognition performance when affected by the variability of non-linear effects …

The olive tree is a highly beneficial fruit tree with the earliest known history of its plantation
going back to 6000 years. The production of olive oil is facing a significant threat nowadays …