Image Processing in Agriculture and Forestry
Image processing in agriculture and forestry represents a challenge towards the automation of tasks for better performances. Agronomists, computer and robotics engineers, and agricultural machinery industry manufacturers now have at their disposal a book containing a collection of methods, procedure...
Format: | eBook |
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Language: | English |
Published: |
MDPI - Multidisciplinary Digital Publishing Institute
2018
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Subjects: | |
Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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003 | oapen | ||
005 | 20210211 | ||
006 | m o d | ||
007 | cr|mn|---annan | ||
008 | 210211s2018 xx |||||o ||| 0|eng d | ||
020 | |a 9783038970972 | ||
020 | |a 9783038970989 | ||
020 | |a books978-3-03897-098-9 | ||
024 | 7 | |a 10.3390/books978-3-03897-098-9 |2 doi | |
040 | |a oapen |c oapen | ||
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a TDCW |2 bicssc | |
720 | 1 | |a Gonzalo Pajares Martinsanz (Ed.) |4 aut | |
720 | 1 | |a Francisco Rovira-Más (Ed.) |4 aut | |
245 | 0 | 0 | |a Image Processing in Agriculture and Forestry |
260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2018 | ||
300 | |a 1 online resource (222 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |f Unrestricted online access |2 star | |
520 | |a Image processing in agriculture and forestry represents a challenge towards the automation of tasks for better performances. Agronomists, computer and robotics engineers, and agricultural machinery industry manufacturers now have at their disposal a book containing a collection of methods, procedures, designs, and descriptions at the technological forefront, which serves as an important support and aid for the implementation and development of their own ideas. The book describes: (1) Applications (canopy on trees, aboveground biomass, phenotyping, chlorophyll, leaf area index, water and nutrient content, land cover change, soil properties, and secure autonomous navigation); (2) Imaging devices onboard robots, unmanned aerial vehicles (UAVs), and satellites operating at different spectral ranges (visible, infrared, hyper-multispectral bands, and radar), as well as guidelines for selecting machine vision systems in outdoor environments; and (3) (Specific computer vision methods (generic and convolutional neural networks, machine learning, specific segmentation approaches, vegetation indices, and three-dimensional (3D) reconstruction). | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |u https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Pharmaceutical chemistry and technology |2 bicssc | |
653 | |a aboreground biomass | ||
653 | |a agriculture | ||
653 | |a autonomous navigation | ||
653 | |a biophysical variables | ||
653 | |a computer vision | ||
653 | |a forestry | ||
653 | |a image processing | ||
653 | |a leaf area index | ||
653 | |a machine-vision | ||
653 | |a vegetation index | ||
793 | 0 | |a DOAB Library. | |
856 | 4 | 0 | |u https://directory.doabooks.org/handle/20.500.12854/49905 |7 0 |z Open Access: DOAB: description of the publication |
856 | 4 | 0 | |u https://www.mdpi.com/books/pdfview/book/714 |7 0 |z Open Access: DOAB, download the publication |