AIMC Topic: Trees

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Assessment of the effects of the biotic and abiotic harmful factors on the amount of industrial wood production with deep learning.

Environmental science and pollution research international Jan 16, 2023
The protection and sustainability of forest assets is possible with planned production of forest products to lead to minimum loss. One of the products obtained from forests is the industrial wood, which is the most important raw material for many sec...
Forests Trees Deep Learning Forestry Wood Conservation of Natural Resources Industry
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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...
Semantics Deep Learning Forests Image Processing, Computer-Assisted Trees
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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 Robotics Forests Remote Sensing Technology Trees
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FractureNet: A 3D Convolutional Neural Network Based on the Architecture of m-Ary Tree for Fracture Type Identification.

IEEE transactions on medical imaging May 2, 2022
To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional neural network (CNN) to learn fracture features from voxelized bone models which are obtained by est...
Humans Neural Networks, Computer Trees
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Tree Trunk Recognition in Orchard Autonomous Operations under Different Light Conditions Using a Thermal Camera and Faster R-CNN.

Sensors (Basel, Switzerland) Mar 7, 2022
In an orchard automation process, a current challenge is to recognize natural landmarks and tree trunks to localize intelligent robots. To overcome low-light conditions and global navigation satellite system (GNSS) signal interruptions under a dense ...
Trees Neural Networks, Computer Japan
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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...
Models, Biological Microbiota Forests Trees RNA, Ribosomal, 16S Bioreactors Machine Learning
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Monitoring Illegal Tree Cutting through Ultra-Low-Power Smart IoT Devices.

Sensors (Basel, Switzerland) Nov 16, 2021
Forests play a fundamental role in preserving the environment and fighting global warming. Unfortunately, they are continuously reduced by human interventions such as deforestation, fires, etc. This paper proposes and evaluates a framework for automa...
Humans Neural Networks, Computer Trees
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Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

The Plant journal : for cell and molecular biology Nov 10, 2021
Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some ...
Computational Biology Nutrients Trees Fruit Bioengineering Artificial Intelligence Climate Change Plant Breeding Vegetables Crops, Agricultural Interdisciplinary Research Flowers Horticulture
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Identifying of Quercus vulcanica and Q. frainetto growing in different environments through deep learning analysis.

Environmental monitoring and assessment Nov 4, 2021
Quercus is one of the important elements of forests worldwide. But the diagnosis of the species in this genus in particular using leaves is pretty challenging due to the presence of natural hybrids and phenotypically plastic trait expression. In this...
Environmental Monitoring Quercus Forests Trees Deep Learning
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Characterizing and forecasting the responses of tropical forest leaf phenology to El Nino by machine learning algorithms.

PloS one Aug 26, 2021
Climate change and global warming have serious adverse impacts on tropical forests. In particular, climate change may induce changes in leaf phenology. However, in tropical dry forests where tree diversity is high, species responses to climate change...
Forests El Nino-Southern Oscillation Algorithms Machine Learning Plant Leaves Trees Tropical Climate Seasons Plant Physiological Phenomena
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