AIMC Topic: Plant Weeds

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Application technology for bioherbicides: challenges and opportunities with dry inoculum and liquid spray formulations.

Pest management science Nov 29, 2023
Bioherbicides offer many potential benefits as part of an integrated weed management system or a totally biological or organic cropping system. A key factor for success is the selection of appropriate formulation and delivery systems for each target ...
Plant Leaves Poaceae Pest Control Robotics Plant Weeds
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Weed Detection Using Deep Learning: A Systematic Literature Review.

Sensors (Basel, Switzerland) Mar 31, 2023
Weeds are one of the most harmful agricultural pests that have a significant impact on crops. Weeds are responsible for higher production costs due to crop waste and have a significant impact on the global agricultural economy. The importance of this...
Artificial Intelligence Plant Weeds Crops, Agricultural Deep Learning Agriculture Weed Control
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Estimation of Off-Target Dicamba Damage on Soybean Using UAV Imagery and Deep Learning.

Sensors (Basel, Switzerland) Mar 19, 2023
Weeds can cause significant yield losses and will continue to be a problem for agricultural production due to climate change. Dicamba is widely used to control weeds in monocot crops, especially genetically engineered dicamba-tolerant (DT) dicot crop...
Unmanned Aerial Devices Dicamba Crops, Agricultural Deep Learning Herbicides Plant Weeds Glycine max Plant Breeding
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Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton.

Scientific reports Nov 15, 2022
Site-specific treatment of weeds in agricultural landscapes has been gaining importance in recent years due to economic savings and minimal impact on the environment. Different detection methods have been developed and tested for precision weed manag...
Gossypium Crops, Agricultural Deep Learning Image Processing, Computer-Assisted Plant Weeds Poaceae Neural Networks, Computer Biomass
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A deep learning-based method for classification, detection, and localization of weeds in turfgrass.

Pest management science Aug 11, 2022
BACKGROUND: Precision spraying of synthetic herbicides can reduce herbicide input. Previous research demonstrated the effectiveness of using image classification neural networks for detecting weeds growing in turfgrass, but did not attempt to discrim...
Weed Control Neural Networks, Computer Deep Learning Plant Weeds Herbicides
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An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms.

Sensors (Basel, Switzerland) Jun 21, 2022
We propose an improved DNN modeling method based on two optimization algorithms, namely the linear decreasing weight particle swarm optimization (LDWPSO) algorithm and invasive weed optimization (IWO) algorithm, for predicting vehicle's longitudinal-...
Neural Networks, Computer Algorithms Computer Simulation Plant Weeds
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Weed Classification from Natural Corn Field-Multi-Plant Images Based on Shallow and Deep Learning.

Sensors (Basel, Switzerland) Apr 14, 2022
Crop and weed discrimination in natural field environments is still challenging for implementing automatic agricultural practices, such as weed control. Some weed control methods have been proposed. However, these methods are still restricted as they...
Plant Weeds Zea mays Weed Control Neural Networks, Computer Deep Learning
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A novel deep learning-based method for detection of weeds in vegetables.

Pest management science Feb 2, 2022
BACKGROUND: Precision weed control in vegetable fields can substantially reduce the required weed control inputs. Rapid and accurate weed detection in vegetable fields is a challenging task due to the presence of a wide variety of weed species at var...
Weed Control Vegetables Crops, Agricultural Deep Learning Plant Weeds
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Weed Classification Using Explainable Multi-Resolution Slot Attention.

Sensors (Basel, Switzerland) Oct 9, 2021
In agriculture, explainable deep neural networks (DNNs) can be used to pinpoint the discriminative part of weeds for an imagery classification task, albeit at a low resolution, to control the weed population. This paper proposes the use of a multi-la...
Plant Weeds Attention Seedlings Neural Networks, Computer Agriculture
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Machine learning models as an alternative to determine productivity losses caused by weeds.

Pest management science Jul 21, 2021
BACKGROUND: Weed control can be economically viable if implemented at the necessary time to minimize interference. Empirical mathematical models have been used to determine when to start the weed control in many crops. Furthermore, empirical models h...
Linear Models Weed Control Machine Learning Neural Networks, Computer Plant Weeds
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