RoboWeedSupport - Presentation of a cloud based system bridging the gap between in-field weed inspections and decision support systems

2017 ◽  
Vol 8 (2) ◽  
pp. 860-864 ◽  
Author(s):  
P. Rydahl ◽  
N.-P. Jensen ◽  
M. Dyrmann ◽  
P. H. Nielsen ◽  
R. N. Jørgensen
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Decision Support Systems ◽  
Convolutional Neural Networks ◽  
Weed Management ◽  
Support Systems ◽  
Integrated Weed Management ◽  
Site Specific ◽  
Large Numbers ◽  
Herbicide Use

In order to exploit potentials of 20–40% reduction of herbicide use, as documented by use of Decision Support Systems (DSS), where requirements for manual field inspection constitute a major obstacle, large numbers of digital pictures of weed infestations have been collected and analysed manually by crop advisors. Results were transferred to: 1) DSS, which determined needs for control and connected, optimized options for control returned options for control and 2) convolutional, neural networks, which in this way were trained to enable automatic analysis of future pictures, which support both field- and site-specific integrated weed management.

scholarly journals Intelligent medical systems in diagnosing and treating inflammatory diseases of the pancreas (systematic review)

2018 ◽  
Vol 39 (1) ◽  
pp. 10-15
Author(s):  
A. A. Litvin
Keyword(s):  
Systematic Review ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Inflammatory Diseases ◽  
Review Of The Literature ◽  
Medical Systems ◽  
Pancreatic Diseases

This paper is a systematic review of the literature on the use of intelligent medical systems in the diagnosis and treatment of acute inflammatory pancreatic diseases. The author provides modern literature data on the efficacy of decision support systems based on artificial neural networks to determine the severity, diagnosis and outcome prognosis of pancreatitis and complications.

scholarly journals Benefits and Limitations of Decision Support Systems (DSS) with a Special Emphasis on Weeds

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 548 ◽  
Author(s):  
Panagiotis Kanatas ◽  
Ilias S. Travlos ◽  
Ioannis Gazoulis ◽  
Alexandros Tataridas ◽  
Anastasia Tsekoura ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Weed Management ◽  
Crop Production ◽  
Support Systems ◽  
Management Strategies ◽  
Farming Systems ◽  
Climatic Conditions ◽  
Management Options ◽  
The Right

Decision support systems (DSS) have the potential to support farmers to make the right decisions in weed management. DSSs can select the appropriate herbicides for a given field and suggest the minimum dose rates for an herbicide application that can result in optimum weed control. Given that the adoption of DSSs may lead to decreased herbicide inputs in crop production, their potential for creating eco-friendly and profitable weed management strategies is obvious and desirable for the re-designing of farming systems on a more sustainable basis. Nevertheless, it is difficult to stimulate farmers to use DSSs as it has been noticed that farmers have different expectations of decision-making tools depending on their farming styles and usual practices. The function of DSSs requires accurate assessments of weeds within a field as input data; however, capturing the data can be problematic. The development of future DSSs should target to enhance weed management tactics which are less reliant on herbicides. DSSs should also provide information regarding weed seedbank dynamics in the soil in order to suggest management options not only within a single period but also in a rotational view. More aspects ought to be taken into account and further research is needed in order to optimize the practical use of DSSs for supporting farmers regarding weed management issues in various crops and under various soil and climatic conditions.

scholarly journals DECISION SUPPORT SYSTEMS IN THE DIAGNOSIS AND TREATMENT OF ACUTE PANCREATITIS

2016 ◽  
pp. 10-17
Author(s):  
A. A. Litvin ◽  
O. Yu. Rebrova
Keyword(s):  
Systematic Review ◽  
Neural Networks ◽  
Decision Making ◽  
Acute Pancreatitis ◽  
Decision Support ◽  
Decision Support Systems ◽  
Pancreatic Necrosis ◽  
Support Systems ◽  
Diagnosis And Treatment ◽  
Review Of Literature

This paper is a systematic review of literature covering the use of decision support systems in the diagnosis and treatment of acute pancreatitis. The authors provide modern literature data on the efficacy of different support systems for decision-making based on artificial neural networks to determine the severity of acute pancreatitis outcomes, prognosis and diagnosis of infected pancreatic necrosis.

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