The digitalization of data has resulted in a data tsunami in practically every industry of data-
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …

In almost every sector, data-driven business, the digitization of the data has generated a
data tsunami. In addition, man-to-machine digital data handling has magnified the …

This paper explores the potential of machine learning algorithms for weed and crop
classification from UAV images. The identification of weeds in crops is a challenging task …

Park managers call for cost-effective and innovative solutions to handle a wide variety of
environmental problems that threaten biodiversity in protected areas. Recently, drones have …

In the era of digital data proliferation, agriculture stands on the cusp of a transformative
revolution driven by Machine Learning (ML). This study delves into the intricate interplay …

Background and aim: Machine learning methods are examined by many researchers to
identify weeds in crop images captured by drones. However, metaheuristic optimization is …

Uncrewed aerial systems (UASs) are becoming very popular in the domain of water
resource map** and management (WRMM). Being a cheaper and quicker option capable …

Climate change and intense anthropogenic activities have heightened the vulnerability of
coastal areas globally. The intensification in the dynamism and uncertainty of coastal …

The application of drones has recently revolutionised the map** of wetlands due to their
high spatial resolution and the flexibility in capturing images. In this study, the drone imagery …

Aquaculture net pen defects such as biofouling, vegetation, and holes are key challenges to
efficient and sustainable fish production in aquaculture. These defects must be monitored to …