AIMC Topic: Unmanned Aerial Devices

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A feature fusion deep-projection convolution neural network for vehicle detection in aerial images.

PloS one
With the rapid development of Unmanned Aerial Vehicles, vehicle detection in aerial images plays an important role in different applications. Comparing with general object detection problems, vehicle detection in aerial images is still a challenging ...

Learning Transferable Driven and Drone Assisted Sustainable and Robust Regional Disease Surveillance for Smart Healthcare.

IEEE/ACM transactions on computational biology and bioinformatics
Smart healthcare has been applied in many fields such as disease surveillance and telemedicine, etc. However, there are some challenges for device deployment, data collection and guarantee of stainability in regional disease surveillance. First, it i...

Detection of pine wood nematode infections in Chinese pine (Pinus tabuliformis) using hyperspectral drone images.

Pest management science
BACKGROUND: The pine wood nematode (PWN) has caused tremendous damage to pine forests in China. Accurately predicting the infestation stage of PWN is crucial for implementing appropriate management, such as chemically controlling early-infested trees...

Estimating canopy leaf angle from leaf to ecosystem scale: a novel deep learning approach using unmanned aerial vehicle imagery.

The New phytologist
Leaf angle distribution (LAD) impacts plant photosynthesis, water use efficiency, and ecosystem primary productivity, which are crucial for understanding surface energy balance and climate change responses. Traditional LAD measurement methods are tim...

Efficient estimation of plant species diversity in desert regions using UAV-based quadrats and advanced machine learning techniques.

Journal of environmental management
Understanding the distribution of plant species diversity(PSD) along spatial and environmental gradients is essential for implementing effective conservation strategies. However, effective monitoring of large-scale PSD in desert regions remain challe...

UAV-based water pollutants detection and classification framework using multi-modal and multi-sensor ensemble learning.

Environmental monitoring and assessment
The massive increment in water pollutants due to the release of plastic, industrial, and household waste has threatened the delicate balance of ecosystems and the well-being of human life. Therefore, detection and monitoring of such water pollutants ...

[Intelligent identification of livestock, a source of infection, based on deep learning of unmanned aerial vehicle images].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
OBJECTIVE: To develop an intelligent recognition model based on deep learning algorithms of unmanned aerial vehicle (UAV) images, and to preliminarily explore the value of this model for remote identification, monitoring and management of cattle, a s...

Different stages of disease detection in squash plant based on machine learning.

Journal of biosciences
To increase agriculture production, accurate and fast detection of plant disease is required. Expert advice is needed to detect disease in plants, nutrition deficiencies or any other abnormalities caused by extreme weather conditions. But this proces...

Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms.

Plant physiology
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but ...