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Remote Sensing Technology

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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...

Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing.

Sensors (Basel, Switzerland)
Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) an...

Digital electronics in fibres enable fabric-based machine-learning inference.

Nature communications
Digital devices are the essential building blocks of any modern electronic system. Fibres containing digital devices could enable fabrics with digital system capabilities for applications in physiological monitoring, human-computer interfaces, and on...

Internet of Things and Robotics in Transforming Current-Day Healthcare Services.

Journal of healthcare engineering
Technology has become an integral part of everyday lives. Recent years have witnessed advancement in technology with a wide range of applications in healthcare. However, the use of the Internet of Things (IoT) and robotics are yet to see substantial ...

A novel semi-supervised framework for UAV based crop/weed classification.

PloS one
Excessive use of agrochemicals for weed controlling infestation has serious agronomic and environmental repercussions associated. An appropriate amount of pesticide/ chemicals is essential for achieving the desired smart farming and precision agricul...

Real-time recognition of spraying area for UAV sprayers using a deep learning approach.

PloS one
Agricultural production is vital for the stability of the country's economy. Controlling weed infestation through agrochemicals is necessary for increasing crop productivity. However, its excessive use has severe repercussions on the environment (dam...

Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields.

PloS one
Crop yield monitoring demonstrated the potential to improve agricultural productivity through improved crop breeding, farm management and commodity planning. Remote and proximal sensing offer the possibility to cut crop monitoring costs traditionally...

A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network.

eLife
Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data...

Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing.

PloS one
Reference evapotranspiration (ETo) is a fundamental parameter for hydrological studies and irrigation management. The Penman-Monteith method is the standard to estimate ETo and requires several meteorological elements. In developing countries, the nu...