Estimation of morphological traits of foliage and effective plant spacing in NFT-based aquaponics system
September 2023
Deep learning and computer vision techniques have gained significant attention in the agriculture sector due to their non-destructive and contactless features. These techniques are also being integrated...
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Low-cost livestock sorting information management system based on deep learning
September 2023
Modern pig farming leaves much to be desired in terms of efficiency, as these systems rely mainly on electromechanical controls and can only categorize pigs according to their weight. This method is...
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Rice disease identification method based on improved CNN-BiGRU
September 2023
In the field of precision agriculture, diagnosing rice diseases from images remains challenging due to high error rates, multiple influencing factors, and unstable conditions. While machine learning...
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Lightweight convolutional neural network models for semantic segmentation of in-field cotton bolls
June 2023
Robotic harvesting of cotton bolls will incorporate the benefits of manual picking as well as mechanical harvesting. For robotic harvesting, in-field cotton segmentation with minimal errors is desirable...
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A deep learning method for monitoring spatial distribution of cage-free hens
June 2023
The spatial distribution of laying hens in cage-free houses is an indicator of flock's health and welfare. While larger space allows chickens to perform more natural behaviors such as dustbathing, foraging,...
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Leguminous seeds detection based on convolutional neural networks: Comparison of Faster R-CNN and YOLOv4 on a small custom dataset
June 2023
This paper help with leguminous seeds detection and smart farming. There are hundreds of kinds of seeds and it can be very difficult to distinguish between them. Botanists and those who study plants,...
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Feature aggregation for nutrient deficiency identification in chili based on machine learning
June 2023
Macronutrient deficiency inhibits the growth and development of chili plants. One of the non-destructive methods that plays a role in processing plant image data based on specific characteristics is...
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How artificial intelligence uses to achieve the agriculture sustainability: Systematic review
June 2023
The generation of food production that meets the rising demand for food and ecosystem security is a big challenge. With the development of Artificial Intelligence (AI) models, there is a growing need...
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GxENet: Novel fully connected neural network based approaches to incorporate GxE for predicting wheat yield
June 2023
The expression of quantitative traits of a line of a crop depends on its genetics, the environment where it is sown and the interaction between the genetic information and the environment known as GxE....
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Deep learning for the detection of semantic features in tree X-ray CT scans
March 2023
According to the industry, the value of wood logs is heavily influenced by their internal structure, particularly the distribution of knots within the trees. Nowadays, CT scanners combined with classical...
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Deep learning models for automatic identification of plant-parasitic nematode
March 2023
Plant-parasitic nematodes cause various diseases that can be fatal to the infected plants. It causes losses to the agricultural industry, such as crop failure and poor crop quality. Developing an accurate...
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A fuzzy risk assessment model used for assessing the introduction of African swine fever into Australia from overseas
March 2023
African swine fever (ASF) is a contagious and lethal hemorrhagic disease with a high case fatality rate. Since 2007, ASF has been spreading into many countries, especially in Europe and Asia. Given...
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Improving the non-destructive maturity classification model for durian fruit using near-infrared spectroscopy
March 2023
The maturity state of durian fruit is a key indicator of quality before trading. This research aims to improve the near-infrared (NIR) model for classifying the maturity stage of durian fruit using...
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Fruit ripeness classification: A survey
March 2023
Fruit is a key crop in worldwide agriculture feeding millions of people. The standard supply chain of fruit products involves quality checks to guarantee freshness, taste, and, most of all, safety....
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t-SNE: A study on reducing the dimensionality of hyperspectral data for the regression problem of estimating oenological parameters
March 2023
In recent years there is a growing importance in using machine learning techniques to improve procedures in precision agriculture: in this work we perform a study on models capable of predicting oenological...
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Effect and economic benefit of precision seeding and laser land leveling for winter wheat in the middle of China
2022
Rapid socio-economic changes in China, such as land conversion and urbanization, are creating new scopes for the application of precision agriculture (PA).An experiment to assess the economic benefits...
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Analysis of land surface temperature using Geospatial technologies in Gida Kiremu, Limu, and Amuru District, Western Ethiopia
2022
Degradation of vegetation cover and expansion of barren land are remained the leading environmental problem at global level. Land surface temperature (LST), Normalized Difference Vegetation Index (NDVI),...
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Non-destructive silkworm pupa gender classification with X-ray images using ensemble learning
2022
Sericulture is the process of cultivating silkworms for the production of silk. High-quality production of silk without mixing with low quality is a great challenge faced in the silk production centers....
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Developing a multi-label tinyML machine learning model for an active and optimized greenhouse microclimate control from multivariate sensed data
2022
In the uncertainties within which the worldwide food security lies nowadays, the agricultural industry is raising a crucial need for being equipped with the state-of-the-art technologies for a more...
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Automatic marker-free registration of single tree point-cloud data based on rotating projection
2022
Point-cloud data acquired using a terrestrial laser scanner play an important role in digital forestry research. Multiple scans are generally used to overcome occlusion effects and obtain complete tree...
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Deep convolutional neural network for damaged vegetation segmentation from RGB images based on virtual NIR-channel estimation
2022
•NIR channel information of damaged vegetation can be estimated from RGB channel.•The use of an adversarial loss increases the performance on NIR channel estimation.•IDCS and IDCR vegetation indices...
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Evaluation of model generalization for growing plants using conditional learning
2022
This paper aims to solve the lack of generalization of existing semantic segmentation models in the crop and weed segmentation domain. We compare two training mechanisms, classical and adversarial,...
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Predicting the true density of commercial biomass pellets using near-infrared hyperspectral imaging
2022
The use of biomass is increasing because it is a form of renewable energy that provides high heating value. Rapid measurements could be used to check the quality of biomass pellets during production....
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Disease detection, severity prediction, and crop loss estimation in MaizeCrop using deep learning
2022
The increasing gap between the demand and productivity of maize crop is a point of concern for the food industry, and farmers. Its' susceptibility to diseases such as Turcicum Leaf Blight, and Rust...
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Explainable artificial intelligence and interpretable machine learning for agricultural data analysis
2022
Artificial intelligence and machine learning have been increasingly applied for prediction in agricultural science. However, many models are typically black boxes, meaning we cannot explain what the...
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