Computers and Electronics in Agriculture
IF
5.57
Papers
5,584
Papers 5,414
1 page of 542 pages (5,414 results)
Newest
#1Marja Haagsma (OSU: Oregon State University)H-Index: 5
#2Gerald F. M. Page (OSU: Oregon State University)H-Index: 6
Last. John S. Selker (OSU: Oregon State University)H-Index: 59
view all 7 authors...
Abstract null null Hyperspectral imaging is useful in identifying plant stress over large areas or with large numbers of individuals. The vast data sets make machine learning indispensable, but the choice of machine-learning model, the accuracy of models in extrapolation over time (dynamic data), and timing of measurements require further elucidation. We assessed two metrics of performance for selection of classification model: the predicted accuracy (PA); and the area under the receiver-operati...
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#1Xinzhi Liu (HFUT: Hefei University of Technology)H-Index: 1
#2Jun Yu (KUT: Kochi University of Technology)H-Index: 4
Last. Shu Zhan (HFUT: Hefei University of Technology)H-Index: 8
view all 6 authors...
Abstract null null Green pepper automatic picking has been a long-standing challenge in agriculture due to the similar color between green peppers and green leaves. To tackle this intractable problem, we tried to distinguish between them by using hyperspectral information as prior knowledge. As our core insight, a novel optical filter was designed as a pre-processing tool to find valuable wavelengths where peppers differ a lot from leaves. To this end, firstly, the parameters of the optical filt...
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#1Goran Stojanovic (University of Novi Sad Faculty of Technical Sciences)H-Index: 19
#2Ankita Sinha (University of Novi Sad Faculty of Technical Sciences)
Last. Maja Radetić (University of Belgrade)H-Index: 25
view all 7 authors...
Abstract null null Present paper demonstrates design and characterization of a textile based microfluidic chip sensor for the detection of milk adulteration through measuring the real part of the impedance and impedance phase angle. Polyamide (PA) based textile fabric was chemically functionalized with polyaniline and titanium dioxide nanoparticles (PANI/TiO2) nanocomposite and embedded in the microfluidic chip. Prototyping of microfluidic chip was performed by xurography and hot lamination usin...
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Abstract null null Counting crop seedlings is a time-demanding activity involved in diverse agricultural practices like plant cultivating, experimental trials, plant breeding procedures, and weed control. Unmanned Aerial Vehicles (UAVs) carrying RGB cameras are novel tools for automatic field mapping, and the analysis of UAV images by deep learning methods can provide relevant agronomic information. UAV-based camera systems and a deep learning image analysis pipeline are implemented for a fully ...
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#1Li Xu (HAU: Hunan Agricultural University)
#2Jiandong Pan (HAU: Hunan Agricultural University)
Last. Wang Xiushan (HAU: Hunan Agricultural University)
view all 8 authors...
Abstract null null In agricultural production, the branches and leaves of green peppers are severely blocked due to the dense plant distribution. This makes the identification of green peppers difficult. Traditional green pepper detection methods entail the problems of low accuracy and poor robustness. This paper introduces a deep learning target detection algorithm based on Yolov4_tiny for green pepper detection. The backbone network in the classic target detection algorithm model is used to en...
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#1Niklas Möhring (University of La Rochelle)H-Index: 9
#2Per Kudsk (AU: Aarhus University)H-Index: 30
Last. Robert Finger (AAEA: Agricultural & Applied Economics Association)H-Index: 34
view all 5 authors...
Abstract null null This paper presents and discusses the “PesticideLoadIndicator” package, a new R-package to compute potential environmental and health effects of pesticide applications using the Danish ‘Pesticide Load’ indicator. The implementation in the R Statistical Language makes it easy for researchers, practitioners and institutions to compare potential pesticide risks for a wide range of applications and compute risk indicators at field-, crop-, farm-, regional- or national level. The t...
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#1Zhe Xing (CAS: Chinese Academy of Sciences)H-Index: 4
#2Changwen Du (CAS: Chinese Academy of Sciences)H-Index: 22
Last. Jianmin Zhou (CAS: Chinese Academy of Sciences)H-Index: 77
view all 5 authors...
Abstract null null Determination of soil organic matter (SOM) is extremely important for diagnosing the fertility status of agricultural soils. Thus, fast and efficient approaches are needed to aid soil fertilization assessment. In this work, the method proposed is based on the combination of mid-infrared attenuated total reflection (FTIR-ATR) and dispersive Raman spectroscopy, as a rapid and nondestructive alternative to traditional chemical analysis. The ability of both two individual and the ...
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#1Tymoteusz Cejrowski (Gdańsk University of Technology)H-Index: 2
#2Julian Szymański (Gdańsk University of Technology)H-Index: 13
Abstract null null Non-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data preparation step for ML models has to be addressed...
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#2L. McClymontH-Index: 6
Last. Ian D. Goodwin (University of Melbourne)H-Index: 41
view all 6 authors...
Abstract null null Modern horticulture is undergoing a rapid change with the introduction of new predictive technologies that help maximise the automation of orchard management practices. This study aimed to calibrate and validate a commercial sensorised mobile platform for the prediction of flower cluster number, fruit number and yield, tree geometry in ‘ANABP-01′ apples. In addition, this work (i) modelled the relationships between tree geometry and light interception, and (ii) determined the ...
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#1Xie Bin (CAU: China Agricultural University)H-Index: 1
#2Weipeng Jiao (CAU: China Agricultural University)H-Index: 1
Last. Junlin Li (CAU: China Agricultural University)H-Index: 1
view all 7 authors...
Abstract null null Due to the variable size of the sheep carcass and the complex characteristics of the surface tissue of the hind legs, the recognition accuracy of the segmented target muscle area is low. This paper proposes a method for detecting the segmentation features of sheep carcass hind legs and carries out a segmentation test to validate it. The approach takes the multi-scale dual attention U-Net (MDAU-Net) semantic segmentation network as its core. It effectively combines different la...
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