AIMC Topic: Farmers

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Analyzing the Relationship among Social Capital, Dynamic Capability, and Farmers' Cooperative Performance Using Lightweight Deep Learning Model: A Case Study of Liaoning Province.

Computational intelligence and neuroscience
The purpose of this study is to understand the relationship between social capital and the performance of Farmers' Cooperatives (Cooperatives) and explore the internal mechanism of social capital affecting the performance of Cooperatives. This work s...

In-Field Automatic Identification of Pomegranates Using a Farmer Robot.

Sensors (Basel, Switzerland)
Ground vehicles equipped with vision-based perception systems can provide a rich source of information for precision agriculture tasks in orchards, including fruit detection and counting, phenotyping, plant growth and health monitoring. This paper pr...

Evolutionary Game Analysis of Farmers' Conservation Tillage Behavior in Black Soil Areas Guided by Deep Learning.

Computational intelligence and neuroscience
To better protect the rights and interests of farmers, the evolutionary game theory and deep learning (DL) technology are used to analyze the conservation tillage behavior of farmers in black soil areas. Firstly, the basic hypotheses are put forward ...

Machine learning models for predicting the use of different animal breeding services in smallholder dairy farms in Sub-Saharan Africa.

Tropical animal health and production
This study is concerned with developing predictive models using machine learning techniques to be used in identifying factors that influence farmers' decisions, predict farmers' decisions, and forecast farmers' demands relating to breeding service. T...

Performance of machine-learning algorithms to pattern recognition and classification of hearing impairment in Brazilian farmers exposed to pesticide and/or cigarette smoke.

Environmental science and pollution research international
The use of pesticides has been increasing in agriculture, leading to a public health problem. The aim of this study was to evaluate ototoxic effects in farmers who were exposed to cigarette smoke and/or pesticides and to identify possible classificat...

Potential dermal and inhalation exposure to imidacloprid and risk assessment among applicators during treatment in cotton field in China.

The Science of the total environment
Quantifying operator exposure to pesticides is a key component of the decision-making procedure for risk assessment. China is the largest cotton-planting country in the world. Dense cotton planting patterns and pesticide overuse potentially place Chi...

Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms.

Environmental science and pollution research international
Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in ru...

Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice.

Scientific reports
Leaf nitrogen content (LNC) is a significant factor which can be utilized to monitor the status of paddy rice and it requires a reliable approach for fast and precise quantification. This investigation aims to quantitatively analyze the correlation b...

Farmers who implemented this, also implemented that: Use of association-rule-learning to improve biosecurity on dairies.

Preventive veterinary medicine
Biosecurity practices are the cornerstone of disease prevention and control programs. In Canada, their implementation is evaluated with a Risk Assessment Questionnaire (RAQ). Association Rule Learning (ARL) - a non-supervised machine learning algorit...