000 | 03619nam a22006495i 4500 | ||
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001 | 978-981-99-4973-1 | ||
003 | DE-He213 | ||
005 | 20240207153709.0 | ||
007 | cr nn 008mamaa | ||
008 | 230920s2023 si | s |||| 0|eng d | ||
020 |
_a9789819949731 _9978-981-99-4973-1 |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
072 | 7 |
_aUYQ _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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072 | 7 |
_aUYQ _2thema |
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082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aWang, Rujing. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aDeep Learning for Agricultural Visual Perception _h[electronic resource] : _bCrop Pest and Disease Detection / _cby Rujing Wang, Lin Jiao, Kang Liu. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2023. |
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300 |
_aXII, 131 p. 1 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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500 | _aAcceso multiusuario | ||
505 | 0 | _aChapter 1. Introduction -- Chapter 2. Deep Learning Technology -- Chapter 3. Large-Scale Agricultural Pest and Disease Datasets -- Chapter 4. Sampling-balanced Region Proposal Network for Pest Detection -- Chapter 5. Crop Pest Detection Methods in Field -- Chapter 6. A CNN-based Arbitrary-oriented Wheat Disease Detection Method. | |
520 | _aThis monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications. | ||
541 |
_fUABC ; _cPerpetuidad |
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650 | 0 | _aArtificial intelligence. | |
650 | 0 |
_aImage processing _xDigital techniques. |
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650 | 0 | _aComputer vision. | |
650 | 0 | _aMachine learning. | |
650 | 0 | _aImage processing. | |
650 | 0 | _aAgriculture. | |
650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aComputer Imaging, Vision, Pattern Recognition and Graphics. |
650 | 2 | 4 | _aComputer Vision. |
650 | 2 | 4 | _aMachine Learning. |
650 | 2 | 4 | _aImage Processing. |
650 | 2 | 4 | _aAgriculture. |
700 | 1 |
_aJiao, Lin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
700 | 1 |
_aLiu, Kang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789819949724 |
776 | 0 | 8 |
_iPrinted edition: _z9789819949748 |
776 | 0 | 8 |
_iPrinted edition: _z9789819949755 |
856 | 4 | 0 |
_zLibro electrónico _uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-99-4973-1 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cLIBRO_ELEC | ||
999 |
_c262674 _d262673 |