AIMC Topic: Plants

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Impacts of speciation and extinction measured by an evolutionary decay clock.

Nature Dec 9, 2020
The hypothesis that destructive mass extinctions enable creative evolutionary radiations (creative destruction) is central to classic concepts of macroevolution. However, the relative impacts of extinction and radiation on the co-occurrence of specie...
Time Factors Plants Machine Learning Animals Fossils Extinction, Biological History, Ancient Genetic Speciation
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Deep Learning Applied to Vegetation Identification and Removal Using Multidimensional Aerial Data.

Sensors (Basel, Switzerland) Oct 30, 2020
When performing structural inspection, the generation of three-dimensional (3D) point clouds is a common resource. Those are usually generated from photogrammetry or through laser scan techniques. However, a significant drawback for complete inspecti...
Deep Learning Motion Plants Photogrammetry
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Plant Leaf Position Estimation with Computer Vision.

Sensors (Basel, Switzerland) Oct 20, 2020
Autonomous analysis of plants, such as for phenotyping and health monitoring etc., often requires the reliable identification and localization of single leaves, a task complicated by their complex and variable shape. Robotic sensor platforms commonly...
Computers Plant Leaves Robotics Algorithms Plants
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Quantifying Tropical Plant Diversity Requires an Integrated Technological Approach.

Trends in ecology & evolution Sep 7, 2020
Tropical biomes are the most diverse plant communities on Earth, and quantifying this diversity at large spatial scales is vital for many purposes. As macroecological approaches proliferate, the taxonomic uncertainties in species occurrence data are ...
Artificial Intelligence Tropical Climate Plants Biodiversity
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Deep Learning Applied to Phenotyping of Biomass in Forages with UAV-Based RGB Imagery.

Sensors (Basel, Switzerland) Aug 26, 2020
Monitoring biomass of forages in experimental plots and livestock farms is a time-consuming, expensive, and biased task. Thus, non-destructive, accurate, precise, and quick phenotyping strategies for biomass yield are needed. To promote high-throughp...
Animal Feed Remote Sensing Technology Plants Livestock Deep Learning Phenotype Animals Biomass Brazil
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Leaf identification using radial basis function neural networks and SSA based support vector machine.

PloS one Aug 19, 2020
In this research, an efficient scheme to identify leaf types is proposed. In that scheme, the leaf boundary points are fitted in a continuous contour using Radial Basis Function Neural Networks (RBFNN) to calculate the centroid of the leaf shape. Aft...
Plant Leaves Neural Networks, Computer Algorithms Plants Support Vector Machine
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Ensemble machine-learning-based framework for estimating total nitrogen concentration in water using drone-borne hyperspectral imagery of emergent plants: A case study in an arid oasis, NW China.

Environmental pollution (Barking, Essex : 1987) Aug 14, 2020
In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality parameters, especially using spectral reflectance of water...
Plants Water Nitrogen Humans Machine Learning China
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Application and Algorithm of Ground-Penetrating Radar for Plant Root Detection: A Review.

Sensors (Basel, Switzerland) May 16, 2020
Attention to the natural environment is equivalent to observing the space in which we live. Plant roots, which are important organs of plants, require our close attention. The method of detecting root system without damaging plants has gradually beco...
Plants Radar Algorithms Machine Learning Plant Roots
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The hunt for sORFs: A multidisciplinary strategy.

Experimental cell research Mar 2, 2020
Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their func...
Protein Sorting Signals Humans Open Reading Frames Animals Ribosomes High-Throughput Nucleotide Sequencing Neural Networks, Computer Computational Biology Proteome Protein Biosynthesis Software Plants
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Deep learning for plant genomics and crop improvement.

Current opinion in plant biology Jan 24, 2020
Our era has witnessed tremendous advances in plant genomics, characterized by an explosion of high-throughput techniques to identify multi-dimensional genome-wide molecular phenotypes at low costs. More importantly, genomics is not merely acquiring m...
Genome, Plant Genomics Phenotype Plants Deep Learning
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