AIMC Topic: Flowers

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Comparison of discriminant methods and deep learning analysis in plant taxonomy: a case study of Elatine.

Scientific reports Nov 28, 2022
Elatine is a genus in which, flower and seed characteristics are the most important diagnostic features; i.e. seed shape and the structure of its cover found to be the most reliable identification character. We used a combination of classic discrimin...
Discriminant Analysis Flowers Malpighiales Deep Learning Seeds
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The Application of RBF Neural Network Model Based on Deep Learning for Flower Pattern Design in Art Teaching.

Computational intelligence and neuroscience Jun 13, 2022
The rapid growth of artificial intelligence technology has been deployed in art teaching and learning. Radial basis function (RBF) networks have a completely different design compared to most neural network architectures. Most neural networks consist...
Deep Learning Flowers Artificial Intelligence Humans Neural Networks, Computer Algorithms
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Deep Neural Networks for Automatic Flower Species Localization and Recognition.

Computational intelligence and neuroscience Apr 29, 2022
Deep neural networks are efficient methods of recognizing image patterns and have been largely implemented in computer vision applications. Object detection has many applications in computer vision, including face and vehicle detection, video surveil...
Neural Networks, Computer Software Flowers
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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 ...
Artificial Intelligence Computational Biology Nutrients Vegetables Flowers Climate Change Trees Fruit Plant Breeding Horticulture Interdisciplinary Research Crops, Agricultural Bioengineering
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Automated color detection in orchids using color labels and deep learning.

PloS one Oct 27, 2021
The color of particular parts of a flower is often employed as one of the features to differentiate between flower types. Thus, color is also used in flower-image classification. Color labels, such as 'green', 'red', and 'yellow', are used by taxonom...
Color Algorithms Flowers Deep Learning Plants
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Machine learning approach for automatic recognition of tomato-pollinating bees based on their buzzing-sounds.

PLoS computational biology Sep 16, 2021
Bee-mediated pollination greatly increases the size and weight of tomato fruits. Therefore, distinguishing between the local set of bees-those that are efficient pollinators-is essential to improve the economic returns for farmers. To achieve this, i...
Crops, Agricultural Pollination Computational Biology Solanum lycopersicum Flowers Bees Acoustics Algorithms Animals Machine Learning
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Can AI distinguish a bone radiograph from photos of flowers or cars? Evaluation of bone age deep learning model on inappropriate data inputs.

Skeletal radiology Aug 5, 2021
OBJECTIVE: To evaluate the behavior of a publicly available deep convolutional neural network (DCNN) bone age algorithm when presented with inappropriate data inputs in both radiological and non-radiological domains.
Neural Networks, Computer Flowers Deep Learning Humans Automobiles Child Radiography
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Can plants fool artificial intelligence? Using machine learning to compare between bee orchids and bees.

Plant signaling & behavior Jun 20, 2021
Bee orchids have long been an excellent example of how dishonest signal works in plant-animal interaction. Many studies compared the flower structures that resemble female bees, leading toward pseudo-copulation of the male bees on the flower. Using M...
Female Animals Orchidaceae Image Processing, Computer-Assisted Artificial Intelligence Male Bees Biological Mimicry Flowers Pollination
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Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus.

Scientific reports Apr 13, 2021
Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. S...
Platycodon Genotyping Techniques Pigmentation Machine Learning Genetic Markers Polymorphism, Single Nucleotide Color Flowers Genotype Transcriptome
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Opposite valence social information provided by bio-robotic demonstrators shapes selection processes in the green bottle fly.

Journal of the Royal Society, Interface Mar 17, 2021
Social learning represents a high-level complex process to acquire information about the environment, which is increasingly reported in invertebrates. The animal-robot interaction paradigm turned out to be an encouraging strategy to unveil social lea...
Behavior, Animal Animals Social Learning Diptera Robotics Flowers
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