AIMC Topic: Forests

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Evaluation of deep learning and transform domain feature extraction techniques for land cover classification: balancing through augmentation.

Environmental science and pollution research international Sep 24, 2022
The identification of features that can improve classification accuracy is a major concern in land cover classification research. This paper compares deep learning and transform domain feature extraction techniques for land cover classification of SA...
Poaceae Forests Agriculture Deep Learning
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Automatic Segmentation of Standing Trees from Forest Images Based on Deep Learning.

Sensors (Basel, Switzerland) Sep 3, 2022
Semantic segmentation of standing trees is important to obtain factors of standing trees from images automatically and effectively. Aiming at the accurate segmentation of multiple standing trees in complex backgrounds, some traditional methods have s...
Deep Learning Trees Semantics Forests Image Processing, Computer-Assisted
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Evaluating the Forest Ecosystem through a Semi-Autonomous Quadruped Robot and a Hexacopter UAV.

Sensors (Basel, Switzerland) Jul 23, 2022
Accurate and timely monitoring is imperative to the resilience of forests for economic growth and climate regulation. In the UK, forest management depends on citizen science to perform tedious and time-consuming data collection tasks. In this study, ...
Ecosystem Forests Trees Remote Sensing Technology Robotics
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Study on TLS Point Cloud Registration Algorithm for Large-Scale Outdoor Weak Geometric Features.

Sensors (Basel, Switzerland) Jul 6, 2022
With the development of societies, the exploitation of mountains and forests is increasing to meet the needs of tourism, mineral resources, and environmental protection. The point cloud registration, 3D modeling, and deformation monitoring that are i...
Tourism Lasers Algorithms Forests Neural Networks, Computer
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Revealing the real-time diversity and abundance of small mammals by using an Intelligent Animal Monitoring System (IAMS).

Integrative zoology Jun 24, 2022
It is challenging to reveal the real-time spatio-temporal change of diversity and abundance of animals in natural systems by using traditional methods. The rapid advancement of new technologies such as the Internet of Things, artificial intelligence,...
Mammals Forests Animals Biodiversity China Artificial Intelligence
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Improving neural network classification of indigenous forest in New Zealand with phenological features.

Journal of environmental management Apr 23, 2022
Accurate and up-to-date land cover maps inform and support effective management and policy decisions. Describing phenological changes in spectral response using time-series data may help to distinguish vegetation types, thereby allowing for more spec...
New Zealand Neural Networks, Computer Forests
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Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions.

Sensors (Basel, Switzerland) Apr 15, 2022
The main impetus for the global efforts toward the current digital transformation in almost all areas of our daily lives is due to the great successes of artificial intelligence (AI), and in particular, the workhorse of AI, statistical machine learni...
Forests Robotics Artificial Intelligence Humans Farms Ecosystem
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Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.

Microbiology spectrum Feb 9, 2022
Microbial community structure is influenced by the environment and in turn exerts control on many environmental parameters. We applied this concept in a bioreactor study to test whether microbial community structure contains information sufficient to...
Microbiota Models, Biological Trees Forests RNA, Ribosomal, 16S Bioreactors Machine Learning
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Forest fire detection system using wireless sensor networks and machine learning.

Scientific reports Jan 7, 2022
Forest fires have become a major threat around the world, causing many negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are some of the consequences of such destruction. Interestingly, a higher perc...
Regression Analysis Remote Sensing Technology Machine Learning Disaster Planning Wireless Technology Wildfires Forests
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Deep diagnostic agent forest (DDAF): A deep learning pathogen recognition system for pneumonia based on CT.

Computers in biology and medicine Dec 16, 2021
BACKGROUND: Even though antibiotics agents are widely used, pneumonia is still one of the most common causes of death around the world. Some severe, fast-spreading pneumonia can even cause huge influence on global economy and life security. In order ...
Deep Learning Forests Pneumonia Retrospective Studies Tomography, X-Ray Computed Humans
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