AIMC Topic: Bees

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A New Initialization Approach in Particle Swarm Optimization for Global Optimization Problems.

Computational intelligence and neuroscience May 17, 2021
Particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search technique used to search for food with the intrinsic manner of bee swarming. PSO is widely used to solve the diverse problems of optimization. Initializat...
Problem Solving Neural Networks, Computer Algorithms Learning Animals Bees
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Assessing the potential for deep learning and computer vision to identify bumble bee species from images.

Scientific reports Apr 7, 2021
Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and compute...
Ecosystem Deep Learning Image Processing, Computer-Assisted Databases, Factual Neural Networks, Computer Animals Artificial Intelligence Species Specificity Pigmentation North America Bees Pollination Conservation of Natural Resources
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Discrimination of Malaysian stingless bee honey from different entomological origins based on physicochemical properties and volatile compound profiles using chemometrics and machine learning.

Food chemistry Jan 15, 2021
Identification of honey origin based on specific chemical markers is important for honey authentication. This study is aimed to differentiate Malaysian stingless bee honey from different entomological origins (Heterotrigona bakeri, Geniotrigona thora...
Phylogeny Cluster Analysis Principal Component Analysis Machine Learning Animals Volatile Organic Compounds Bees Least-Squares Analysis Discriminant Analysis Honey
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Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence.

Neural plasticity Jan 13, 2021
Unmanned autonomous helicopter (UAH) path planning problem is an important component of the UAH mission planning system. The performance of the automatic path planner determines the quality of the UAH flight path. Aiming to produce a high-quality fli...
Animals Aircraft Bees Brain-Computer Interfaces Flight, Animal Artificial Intelligence Algorithms Computer Simulation Humans
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In silico prediction of chemical acute contact toxicity on honey bees via machine learning methods.

Toxicology in vitro : an international journal published in association with BIBRA Jan 11, 2021
In recent years, the decline of honey bees and the collapse of bee colonies have caught the attention of ecologists, and the use of pesticides is one of the main reasons for the decline. Therefore, ecological risk assessment of pesticides is essentia...
Machine Learning Risk Assessment Models, Theoretical Bees Pesticides Computer Simulation Quantitative Structure-Activity Relationship Animals Lethal Dose 50 Toxicity Tests, Acute
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A bioinspired angular velocity decoding neural network model for visually guided flights.

Neural networks : the official journal of the International Neural Network Society Dec 28, 2020
Efficient and robust motion perception systems are important pre-requisites for achieving visually guided flights in future micro air vehicles. As a source of inspiration, the visual neural networks of flying insects such as honeybee and Drosophila p...
Neural Networks, Computer Animals Virtual Reality Visual Pathways Bees Neurons Flight, Animal Insecta Motion Perception
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Reconfigurable Particle Swarm Robotics Powered by Acoustic Vibration Tweezer.

Soft robotics Nov 20, 2020
Inspired by natural swarms such as bees and ants, various types of swarm robotic systems have been developed to work together to complete tasks that transcend individual capabilities. Autonomous robots controlled by collective algorithm and colloidal...
Bees Vibration Robotics Algorithms Equipment Design Animals Acoustics
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Cross Lingual Sentiment Analysis: A Clustering-Based Bee Colony Instance Selection and Target-Based Feature Weighting Approach.

Sensors (Basel, Switzerland) Sep 15, 2020
The lack of sentiment resources in poor resource languages poses challenges for the sentiment analysis in which machine learning is involved. Cross-lingual and semi-supervised learning approaches have been deployed to represent the most common ways t...
Supervised Machine Learning Bees Machine Learning Animals Algorithms Cluster Analysis Language
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Benefits of insect colours: a review from social insect studies.

Oecologia Sep 2, 2020
Insect colours assist in body protection, signalling, and physiological adaptations. Colours also convey multiple channels of information. These channels are valuable for species identification, distinguishing individual quality, and revealing ecolog...
Artificial Intelligence Insecta Animals Bees Ecosystem Biological Evolution Color
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A framework based on deep neural networks to extract anatomy of mosquitoes from images.

Scientific reports Aug 3, 2020
We design a framework based on Mask Region-based Convolutional Neural Network to automatically detect and separately extract anatomical components of mosquitoes-thorax, wings, abdomen and legs from images. Our training dataset consisted of 1500 smart...
Animals Anatomic Landmarks Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted Bees Culicidae
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