AIMC Topic: Pollination

Clear Filters Showing 11 to 20 of 23 articles

Wearable Sensors Assess the Effects of Human-Robot Collaboration in Simulated Pollination.

Sensors (Basel, Switzerland)
Pollination for indoor agriculture is hampered by environmental conditions, requiring farmers to pollinate manually. This increases the musculoskeletal illness risk of workers. A potential solution involves Human-Robot Collaboration (HRC) using weara...

Deep SE-BiLSTM with IFPOA Fine-Tuning for Human Activity Recognition Using Mobile and Wearable Sensors.

Sensors (Basel, Switzerland)
Pervasive computing, human-computer interaction, human behavior analysis, and human activity recognition (HAR) fields have grown significantly. Deep learning (DL)-based techniques have recently been effectively used to predict various human actions u...

A search and rescue robot search method based on flower pollination algorithm and Q-learning fusion algorithm.

PloS one
Search algorithm plays an important role in the motion planning of the robot, it determines whether the mobile robot complete the task. To solve the search task in complex environments, a fusion algorithm based on the Flower Pollination algorithm and...

Shape classification technology of pollinated tomato flowers for robotic implementation.

Scientific reports
Three pollination methods are commonly used in the greenhouse cultivation of tomato. These are pollination using insects, artificial pollination (by manually vibrating flowers), and plant growth regulators. Insect pollination is the preferred natural...

Machine learning approach for automatic recognition of tomato-pollinating bees based on their buzzing-sounds.

PLoS computational biology
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...

Can plants fool artificial intelligence? Using machine learning to compare between bee orchids and bees.

Plant signaling & behavior
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...

Assessing the potential for deep learning and computer vision to identify bumble bee species from images.

Scientific reports
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...

Pollen analysis using multispectral imaging flow cytometry and deep learning.

The New phytologist
Pollen identification and quantification are crucial but challenging tasks in addressing a variety of evolutionary and ecological questions (pollination, paleobotany), but also for other fields of research (e.g. allergology, honey analysis or forensi...

An Amazon stingless bee foraging activity predicted using recurrent artificial neural networks and attribute selection.

Scientific reports
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...

Robotic bees for crop pollination: Why drones cannot replace biodiversity.

The Science of the total environment
The notion that robotic crop pollination will solve the decline in pollinators has gained wide popularity recently (Fig. 1), and in March 2018 Walmart filed a patent for autonomous robot bees. However, w present six arguments showing that this is a t...