Advances in Hyperspectral Data Exploitation
Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such appli...
Saved in:
| HerausgeberIn: | |
|---|---|
| Sonstige: | |
| Year of Publication: | 2022 |
| Language: | English |
| Physical Description: | 1 electronic resource (434 p.) |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
993573553404498 |
|---|---|
| ctrlnum |
(CKB)5470000001631715 (oapen)https://directory.doabooks.org/handle/20.500.12854/94557 (EXLCZ)995470000001631715 |
| collection |
bib_alma |
| record_format |
marc |
| spelling |
Chang, Chein-I edt Advances in Hyperspectral Data Exploitation Basel MDPI - Multidisciplinary Digital Publishing Institute 2022 1 electronic resource (434 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Open access Unrestricted online access star Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such applications may include water pollution and toxic waste in environmental monitoring, pesticide residual detection in food safety and inspection, plant and crop disease detection in agriculture, tumor detection and breast cancer detection in medical imaging, drug traffic in law enforcement, etc. Nevertheless, this reprint book provides many techniques which may find their ways in these applications as well. English Technology: general issues bicssc History of engineering & technology bicssc hyperspectral image few-shot classification deep learning meta-learning relation network convolutional neural network constrained-target optimal index factor band selection (CTOIFBS) hyperspectral image underwater spectral imaging system underwater hyperspectral target detection band selection (BS) constrained energy minimization (CEM) lightweight convolutional neural networks hyperspectral imagery classification transfer learning air temperature spatial measurement FTIR MWIR carbon dioxide absorption target detection coffee beans insect damage hyperspectral imaging band selection visualization color formation models multispectral image image fusion joint tensor decomposition anomaly detection constrained sparse representation hyperspectral imagery moving target detection spatio-temporal processing hyperspectral remote sensing image classification constraint representation superpixel segmentation multiscale decision fusion plug-and-play denoising nonlinear unmixing spectral reconstruction residual augmented attentional u-shape network spatial augmented attention channel augmented attention boundary-aware constraint atmospheric transmittance temperature emissivity separation midwave infrared hyperspectral images hyperspectral image super-resolution data fusion spectral-spatial residual network self-supervised training hyperspectral vegetation generative adversarial network data augmentation classification rice leaf blast hyperspectral imaging data deep convolutional neural networks fused features evolutionary computation heuristic algorithms machine learning unmanned aerial vehicles (UAVs) vegetation mapping upland swamps mine environment rice rice leaf folder hyperspectral image classification change detection self-supervised learning attention mechanism multi-source image fusion SFIM least square estimation spatial filter hyperspectral imaging (HSI) hyperspectral target detection hyperspectral reconstruction hyperspectral unmixing 3-0365-5795-4 Song, Meiping edt Yu, Chunyan edt Wang, Yulei edt Yu, Haoyang edt Li, Jiaojiao edt Wang, Lin edt Li, Hsiao-Chi edt Li, Xiaorun edt Chang, Chein-I oth Song, Meiping oth Yu, Chunyan oth Wang, Yulei oth Yu, Haoyang oth Li, Jiaojiao oth Wang, Lin oth Li, Hsiao-Chi oth Li, Xiaorun oth |
| language |
English |
| format |
eBook |
| author2 |
Song, Meiping Yu, Chunyan Wang, Yulei Yu, Haoyang Li, Jiaojiao Wang, Lin Li, Hsiao-Chi Li, Xiaorun Chang, Chein-I Song, Meiping Yu, Chunyan Wang, Yulei Yu, Haoyang Li, Jiaojiao Wang, Lin Li, Hsiao-Chi Li, Xiaorun |
| author_facet |
Song, Meiping Yu, Chunyan Wang, Yulei Yu, Haoyang Li, Jiaojiao Wang, Lin Li, Hsiao-Chi Li, Xiaorun Chang, Chein-I Song, Meiping Yu, Chunyan Wang, Yulei Yu, Haoyang Li, Jiaojiao Wang, Lin Li, Hsiao-Chi Li, Xiaorun |
| author2_variant |
c i c cic m s ms c y cy y w yw h y hy j l jl l w lw h c l hcl x l xl |
| author2_role |
HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn Sonstige Sonstige Sonstige Sonstige Sonstige Sonstige Sonstige Sonstige Sonstige |
| title |
Advances in Hyperspectral Data Exploitation |
| spellingShingle |
Advances in Hyperspectral Data Exploitation |
| title_full |
Advances in Hyperspectral Data Exploitation |
| title_fullStr |
Advances in Hyperspectral Data Exploitation |
| title_full_unstemmed |
Advances in Hyperspectral Data Exploitation |
| title_auth |
Advances in Hyperspectral Data Exploitation |
| title_new |
Advances in Hyperspectral Data Exploitation |
| title_sort |
advances in hyperspectral data exploitation |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2022 |
| physical |
1 electronic resource (434 p.) |
| isbn |
3-0365-5796-2 3-0365-5795-4 |
| illustrated |
Not Illustrated |
| work_keys_str_mv |
AT changcheini advancesinhyperspectraldataexploitation AT songmeiping advancesinhyperspectraldataexploitation AT yuchunyan advancesinhyperspectraldataexploitation AT wangyulei advancesinhyperspectraldataexploitation AT yuhaoyang advancesinhyperspectraldataexploitation AT lijiaojiao advancesinhyperspectraldataexploitation AT wanglin advancesinhyperspectraldataexploitation AT lihsiaochi advancesinhyperspectraldataexploitation AT lixiaorun advancesinhyperspectraldataexploitation |
| status_str |
n |
| ids_txt_mv |
(CKB)5470000001631715 (oapen)https://directory.doabooks.org/handle/20.500.12854/94557 (EXLCZ)995470000001631715 |
| carrierType_str_mv |
cr |
| is_hierarchy_title |
Advances in Hyperspectral Data Exploitation |
| author2_original_writing_str_mv |
noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField noLinkedField |
| _version_ |
1796652572421914624 |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05614nam-a2201549z--4500</leader><controlfield tag="001">993573553404498</controlfield><controlfield tag="005">20231214133157.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr|mn|---annan</controlfield><controlfield tag="008">202212s2022 xx |||||o ||| 0|eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3-0365-5796-2</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)5470000001631715</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/94557</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)995470000001631715</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chang, Chein-I</subfield><subfield code="4">edt</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Advances in Hyperspectral Data Exploitation</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="a">Basel</subfield><subfield code="b">MDPI - Multidisciplinary Digital Publishing Institute</subfield><subfield code="c">2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 electronic resource (434 p.)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="506" ind1=" " ind2=" "><subfield code="a">Open access</subfield><subfield code="f">Unrestricted online access</subfield><subfield code="2">star</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such applications may include water pollution and toxic waste in environmental monitoring, pesticide residual detection in food safety and inspection, plant and crop disease detection in agriculture, tumor detection and breast cancer detection in medical imaging, drug traffic in law enforcement, etc. Nevertheless, this reprint book provides many techniques which may find their ways in these applications as well.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Technology: general issues</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">History of engineering & technology</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral image few-shot classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">deep learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">meta-learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">relation network</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">convolutional neural network</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">constrained-target optimal index factor band selection (CTOIFBS)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral image</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">underwater spectral imaging system</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">underwater hyperspectral target detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">band selection (BS)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">constrained energy minimization (CEM)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">lightweight convolutional neural networks</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral imagery classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">transfer learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">air temperature</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spatial measurement</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">FTIR</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">MWIR</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">carbon dioxide absorption</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">target detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">coffee beans</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">insect damage</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral imaging</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">band selection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">visualization</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">color formation models</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">multispectral image</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">image fusion</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">joint tensor decomposition</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">anomaly detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">constrained sparse representation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral imagery</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">moving target detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spatio-temporal processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral remote sensing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">image classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">constraint representation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">superpixel segmentation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">multiscale decision fusion</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">plug-and-play</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">denoising</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">nonlinear unmixing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spectral reconstruction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">residual augmented attentional u-shape network</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spatial augmented attention</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">channel augmented attention</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">boundary-aware constraint</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">atmospheric transmittance</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">temperature</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">emissivity</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">separation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">midwave infrared</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral images</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral image super-resolution</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data fusion</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spectral-spatial residual network</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">self-supervised training</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">vegetation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">generative adversarial network</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data augmentation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rice leaf blast</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral imaging data</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">deep convolutional neural networks</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">fused features</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">evolutionary computation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">heuristic algorithms</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">machine learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">unmanned aerial vehicles (UAVs)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">vegetation mapping</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">upland swamps</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">mine environment</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rice</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rice leaf folder</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral image classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">change detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">self-supervised learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">attention mechanism</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">multi-source image fusion</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">SFIM</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">least square estimation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spatial filter</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral imaging (HSI)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral target detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral reconstruction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hyperspectral unmixing</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-5795-4</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Song, Meiping</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yu, Chunyan</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Yulei</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yu, Haoyang</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Jiaojiao</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Lin</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Hsiao-Chi</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Xiaorun</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chang, Chein-I</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Song, Meiping</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yu, Chunyan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Yulei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yu, Haoyang</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Jiaojiao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Lin</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Hsiao-Chi</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Xiaorun</subfield><subfield code="4">oth</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-12-15 05:45:45 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2023-01-09 04:44:33 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5341785590004498&Force_direct=true</subfield><subfield code="Z">5341785590004498</subfield><subfield code="b">Available</subfield><subfield code="8">5341785590004498</subfield></datafield></record></collection> |