AIMC Topic: Bees
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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...
An Amazon stingless bee foraging activity predicted using recurrent artificial neural networks and attribute selection.
Scientific reports
Jan 8, 2020
Bees play a key role in pollination of crops and in diverse ecosystems. There have been multiple reports in recent years illustrating bee population declines worldwide. The search for more accurate forecast models can aid both in the understanding of...
Global transcriptome analysis reveals relevant effects at environmental concentrations of cypermethrin in honey bees (Apis mellifera).
Environmental pollution (Barking, Essex : 1987)
Dec 4, 2019
Cypermethrin is a frequently used insecticide in agriculture and households but its chronic and molecular effects are poorly known are . Here we describe effects of sublethal cypermethrin exposure on the global transcriptome in the brain of honey bee...
Hybrid Artificial Bee Colony Algorithm for a Parallel Batching Distributed Flow-Shop Problem With Deteriorating Jobs.
IEEE transactions on cybernetics
Oct 8, 2019
In this article, we propose a hybrid artificial bee colony (ABC) algorithm to solve a parallel batching distributed flow-shop problem (DFSP) with deteriorating jobs. In the considered problem, there are two stages as follows: 1) in the first stage, a...
Unsupervised machine learning reveals mimicry complexes in bumblebees occur along a perceptual continuum.
Proceedings. Biological sciences
Sep 11, 2019
Müllerian mimicry theory states that frequency-dependent selection should favour geographical convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes, each cont...
A Transition Control Mechanism for Artificial Bee Colony (ABC) Algorithm.
Computational intelligence and neuroscience
Apr 1, 2019
Artificial Bee Colony (ABC) algorithm inspired by the complex search and foraging behaviors of real honey bees is one of the most promising implementations of the Swarm Intelligence- (SI-) based optimization algorithms. Due to its robust and phase-di...
An Optimization Framework of Multiobjective Artificial Bee Colony Algorithm Based on the MOEA Framework.
Computational intelligence and neuroscience
Nov 1, 2018
The artificial bee colony (ABC) algorithm has become one of the popular optimization metaheuristics and has been proven to perform better than many state-of-the-art algorithms for dealing with complex multiobjective optimization problems. However, th...
Abstract concept learning in a simple neural network inspired by the insect brain.
PLoS computational biology
Sep 17, 2018
The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly h...
Reinforcement learning for solution updating in Artificial Bee Colony.
PloS one
Jul 17, 2018
In the Artificial Bee Colony (ABC) algorithm, the employed bee and the onlooker bee phase involve updating the candidate solutions by changing a value in one dimension, dubbed one-dimension update process. For some problems which the number of dimens...
Achieving bioinspired flapping wing hovering flight solutions on Mars via wing scaling.
Bioinspiration & biomimetics
Jun 26, 2018
Achieving atmospheric flight on Mars is challenging due to the low density of the Martian atmosphere. Aerodynamic forces are proportional to the atmospheric density, which limits the use of conventional aircraft designs on Mars. Here, we show using n...
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