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Conservation of Natural Resources

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Deep neural networks based automated extraction of dugong feeding trails from UAV images in the intertidal seagrass beds.

PloS one
Dugongs (Dugong dugon) are seagrass specialists distributed in shallow coastal waters in tropical and subtropical seas. The area and distribution of the dugongs' feeding trails, which are unvegetated winding tracks left after feeding, have been used ...

Leveraging social media and deep learning to detect rare megafauna in video surveys.

Conservation biology : the journal of the Society for Conservation Biology
Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys p...

Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China.

The Science of the total environment
Land use (LU) changes caused by urbanization, climate, and anthropogenic activities alter the supply of ecosystem services (ES), which affects the ecological service value (ESV) of a given region. Existing LU simulation models extract neighborhood ef...

Towards sustainable demersal fisheries: NepCon image acquisition system for automatic Nephrops norvegicus detection.

PloS one
Underwater video monitoring systems are being widely used in fisheries to investigate fish behavior in relation to fishing gear and fishing gear performance during fishing. Such systems can be useful to evaluate the catch composition as well. In deme...

Developing machine learning models for relative humidity prediction in air-based energy systems and environmental management applications.

Journal of environmental management
The prediction of relative humidity is a challenging task because of its nonlinear nature. The machine learning-based prediction strategies have attained significant attention in tackling a broad class of challenging nonlinear and complex problems. T...

Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas.

Sensors (Basel, Switzerland)
The world's oceans are one of the most valuable sources of biodiversity and resources on the planet, although there are areas where the marine ecosystem is threatened by human activities. Marine protected areas (MPAs) are distinctive spaces protected...

Assessing the potential for deep learning and computer vision to identify bumble bee species from images.

Scientific reports
Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and compute...

Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility.

Journal of environmental management
The objective of this study is to assess the gully head-cut erosion susceptibility and identify gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area has been greatly influenced by several head-cut gullies due to ...

Automated conservation assessment of the orchid family with deep learning.

Conservation biology : the journal of the Society for Conservation Biology
International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation ass...

The use of machine learning to detect foraging behaviour in whale sharks: a new tool in conservation.

Journal of fish biology
In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri-axial accelerometers and their foraging behaviours were visually...