Smart Sensing Technologies for Agriculture
"Smart Sensing Technologies for Agriculture" is a Special Issue of Sensors that includes 14 research papers on diverse topics about the measurement of physical, chemical, and biological characteristics of soil, plants, and animals related to modern farming practices.
Format: | eBook |
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Language: | English |
Published: |
Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2020
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Subjects: | |
Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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072 | 7 | |a TBX |2 bicssc | |
720 | 1 | |a Adamchuk, Viacheslav |4 edt | |
720 | 1 | |a Adamchuk, Viacheslav |4 oth | |
720 | 1 | |a Biswas, Asim |4 edt | |
720 | 1 | |a Biswas, Asim |4 oth | |
720 | 1 | |a Sudduth, Kenneth |4 edt | |
720 | 1 | |a Sudduth, Kenneth |4 oth | |
245 | 0 | 0 | |a Smart Sensing Technologies for Agriculture |
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650 | 7 | |a History of engineering and technology |2 bicssc | |
653 | |a adaptive K-means | ||
653 | |a apparent electrical conductivity (ECa) | ||
653 | |a autonomous robot | ||
653 | |a body dimensions | ||
653 | |a boundary-line | ||
653 | |a broiler surface temperature extraction | ||
653 | |a cation exchange capacity | ||
653 | |a clay content | ||
653 | |a convolutional neural networks | ||
653 | |a crop protection | ||
653 | |a cutting point detection | ||
653 | |a deep learning | ||
653 | |a droplet characterization | ||
653 | |a elemental composition | ||
653 | |a ellipse fitting | ||
653 | |a feature recognition | ||
653 | |a FFPH | ||
653 | |a germination paper | ||
653 | |a gripper | ||
653 | |a harvesting robot | ||
653 | |a head region locating | ||
653 | |a infrared spectroscopy | ||
653 | |a ion-selective electrode (ISE) | ||
653 | |a Kalman filter | ||
653 | |a Kd-network | ||
653 | |a kinetic stereo imaging | ||
653 | |a laser-induced breakdown spectroscopy | ||
653 | |a law of minimum | ||
653 | |a LIBS | ||
653 | |a livestock | ||
653 | |a lying posture | ||
653 | |a machine vision | ||
653 | |a mapping | ||
653 | |a model predictive control | ||
653 | |a moisture measurement | ||
653 | |a multispectral imaging | ||
653 | |a non-contact measurement | ||
653 | |a on-site detection | ||
653 | |a optical micro-sensors | ||
653 | |a partial least squares (PLS) | ||
653 | |a pH | ||
653 | |a plant detection | ||
653 | |a point cloud | ||
653 | |a precision agriculture | ||
653 | |a precision farming | ||
653 | |a precision weeding | ||
653 | |a principal component analysis (PCA) | ||
653 | |a proximal soil sensing | ||
653 | |a quantile regression | ||
653 | |a quasi-3D inversion algorithm | ||
653 | |a real-time measurement | ||
653 | |a sandy infertile soil | ||
653 | |a segmentation | ||
653 | |a sensor fusion | ||
653 | |a soil | ||
653 | |a soil electrical resistivity | ||
653 | |a soil moisture | ||
653 | |a soil nitrate nitrogen (NO3−-N) | ||
653 | |a soil nutrients | ||
653 | |a soil testing | ||
653 | |a spectroscopy | ||
653 | |a standing posture | ||
653 | |a thermal image processing | ||
653 | |a Three-dimensional mapping | ||
653 | |a transfer learning | ||
653 | |a UAV | ||
653 | |a willow tree | ||
653 | |a X-ray fluorescence | ||
653 | |a yield estimation | ||
793 | 0 | |a DOAB Library. | |
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856 | 4 | 0 | |u https://mdpi.com/books/pdfview/book/2722 |7 0 |z Open Access: DOAB, download the publication |