Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation
• Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hettiarachchi, R. [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Schlagwörter: |
|---|
| Umfang: |
17 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Propolis as lipid bioactive nano-carrier for topical nasal drug delivery - Rassu, Giovanna ELSEVIER, 2015, Orlando, Fla |
|---|---|
| Übergeordnetes Werk: |
volume:41 ; year:2016 ; pages:123-139 ; extent:17 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.jvcir.2016.09.011 |
|---|
| Katalog-ID: |
ELV035492554 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV035492554 | ||
| 003 | DE-627 | ||
| 005 | 20230624022542.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 180603s2016 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.jvcir.2016.09.011 |2 doi | |
| 028 | 5 | 2 | |a GBVA2016018000023.pica |
| 035 | |a (DE-627)ELV035492554 | ||
| 035 | |a (ELSEVIER)S1047-3203(16)30201-2 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | |a 620 | |
| 082 | 0 | 4 | |a 620 |q DE-600 |
| 082 | 0 | 4 | |a 540 |q VZ |
| 082 | 0 | 4 | |a 540 |q VZ |
| 100 | 1 | |a Hettiarachchi, R. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation |
| 264 | 1 | |c 2016 | |
| 300 | |a 17 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a • Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. | ||
| 650 | 7 | |a Skin segmentation |2 Elsevier | |
| 650 | 7 | |a Multi-manifold learning |2 Elsevier | |
| 650 | 7 | |a Feature space Voronoï segmentation |2 Elsevier | |
| 700 | 1 | |a Peters, J.F. |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Academic Press |a Rassu, Giovanna ELSEVIER |t Propolis as lipid bioactive nano-carrier for topical nasal drug delivery |d 2015 |g Orlando, Fla |w (DE-627)ELV023814993 |
| 773 | 1 | 8 | |g volume:41 |g year:2016 |g pages:123-139 |g extent:17 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.jvcir.2016.09.011 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a GBV_ILN_11 | ||
| 912 | |a GBV_ILN_21 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_50 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_72 | ||
| 912 | |a GBV_ILN_136 | ||
| 912 | |a GBV_ILN_162 | ||
| 912 | |a GBV_ILN_165 | ||
| 912 | |a GBV_ILN_176 | ||
| 912 | |a GBV_ILN_181 | ||
| 912 | |a GBV_ILN_203 | ||
| 912 | |a GBV_ILN_227 | ||
| 912 | |a GBV_ILN_352 | ||
| 912 | |a GBV_ILN_676 | ||
| 912 | |a GBV_ILN_791 | ||
| 912 | |a GBV_ILN_1018 | ||
| 951 | |a AR | ||
| 952 | |d 41 |j 2016 |h 123-139 |g 17 | ||
| 953 | |2 045F |a 620 | ||
| author_variant |
r h rh |
|---|---|
| matchkey_str |
hettiarachchirpetersjf:2016----:utmnflbsdknlsiirnetrsaeoooei |
| hierarchy_sort_str |
2016 |
| publishDate |
2016 |
| allfields |
10.1016/j.jvcir.2016.09.011 doi GBVA2016018000023.pica (DE-627)ELV035492554 (ELSEVIER)S1047-3203(16)30201-2 DE-627 ger DE-627 rakwb eng 620 620 DE-600 540 VZ 540 VZ Hettiarachchi, R. verfasserin aut Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation 2016 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Elsevier Peters, J.F. oth Enthalten in Academic Press Rassu, Giovanna ELSEVIER Propolis as lipid bioactive nano-carrier for topical nasal drug delivery 2015 Orlando, Fla (DE-627)ELV023814993 volume:41 year:2016 pages:123-139 extent:17 https://doi.org/10.1016/j.jvcir.2016.09.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_50 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_136 GBV_ILN_162 GBV_ILN_165 GBV_ILN_176 GBV_ILN_181 GBV_ILN_203 GBV_ILN_227 GBV_ILN_352 GBV_ILN_676 GBV_ILN_791 GBV_ILN_1018 AR 41 2016 123-139 17 045F 620 |
| spelling |
10.1016/j.jvcir.2016.09.011 doi GBVA2016018000023.pica (DE-627)ELV035492554 (ELSEVIER)S1047-3203(16)30201-2 DE-627 ger DE-627 rakwb eng 620 620 DE-600 540 VZ 540 VZ Hettiarachchi, R. verfasserin aut Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation 2016 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Elsevier Peters, J.F. oth Enthalten in Academic Press Rassu, Giovanna ELSEVIER Propolis as lipid bioactive nano-carrier for topical nasal drug delivery 2015 Orlando, Fla (DE-627)ELV023814993 volume:41 year:2016 pages:123-139 extent:17 https://doi.org/10.1016/j.jvcir.2016.09.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_50 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_136 GBV_ILN_162 GBV_ILN_165 GBV_ILN_176 GBV_ILN_181 GBV_ILN_203 GBV_ILN_227 GBV_ILN_352 GBV_ILN_676 GBV_ILN_791 GBV_ILN_1018 AR 41 2016 123-139 17 045F 620 |
| allfields_unstemmed |
10.1016/j.jvcir.2016.09.011 doi GBVA2016018000023.pica (DE-627)ELV035492554 (ELSEVIER)S1047-3203(16)30201-2 DE-627 ger DE-627 rakwb eng 620 620 DE-600 540 VZ 540 VZ Hettiarachchi, R. verfasserin aut Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation 2016 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Elsevier Peters, J.F. oth Enthalten in Academic Press Rassu, Giovanna ELSEVIER Propolis as lipid bioactive nano-carrier for topical nasal drug delivery 2015 Orlando, Fla (DE-627)ELV023814993 volume:41 year:2016 pages:123-139 extent:17 https://doi.org/10.1016/j.jvcir.2016.09.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_50 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_136 GBV_ILN_162 GBV_ILN_165 GBV_ILN_176 GBV_ILN_181 GBV_ILN_203 GBV_ILN_227 GBV_ILN_352 GBV_ILN_676 GBV_ILN_791 GBV_ILN_1018 AR 41 2016 123-139 17 045F 620 |
| allfieldsGer |
10.1016/j.jvcir.2016.09.011 doi GBVA2016018000023.pica (DE-627)ELV035492554 (ELSEVIER)S1047-3203(16)30201-2 DE-627 ger DE-627 rakwb eng 620 620 DE-600 540 VZ 540 VZ Hettiarachchi, R. verfasserin aut Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation 2016 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Elsevier Peters, J.F. oth Enthalten in Academic Press Rassu, Giovanna ELSEVIER Propolis as lipid bioactive nano-carrier for topical nasal drug delivery 2015 Orlando, Fla (DE-627)ELV023814993 volume:41 year:2016 pages:123-139 extent:17 https://doi.org/10.1016/j.jvcir.2016.09.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_50 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_136 GBV_ILN_162 GBV_ILN_165 GBV_ILN_176 GBV_ILN_181 GBV_ILN_203 GBV_ILN_227 GBV_ILN_352 GBV_ILN_676 GBV_ILN_791 GBV_ILN_1018 AR 41 2016 123-139 17 045F 620 |
| allfieldsSound |
10.1016/j.jvcir.2016.09.011 doi GBVA2016018000023.pica (DE-627)ELV035492554 (ELSEVIER)S1047-3203(16)30201-2 DE-627 ger DE-627 rakwb eng 620 620 DE-600 540 VZ 540 VZ Hettiarachchi, R. verfasserin aut Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation 2016 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Elsevier Peters, J.F. oth Enthalten in Academic Press Rassu, Giovanna ELSEVIER Propolis as lipid bioactive nano-carrier for topical nasal drug delivery 2015 Orlando, Fla (DE-627)ELV023814993 volume:41 year:2016 pages:123-139 extent:17 https://doi.org/10.1016/j.jvcir.2016.09.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_50 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_136 GBV_ILN_162 GBV_ILN_165 GBV_ILN_176 GBV_ILN_181 GBV_ILN_203 GBV_ILN_227 GBV_ILN_352 GBV_ILN_676 GBV_ILN_791 GBV_ILN_1018 AR 41 2016 123-139 17 045F 620 |
| language |
English |
| source |
Enthalten in Propolis as lipid bioactive nano-carrier for topical nasal drug delivery Orlando, Fla volume:41 year:2016 pages:123-139 extent:17 |
| sourceStr |
Enthalten in Propolis as lipid bioactive nano-carrier for topical nasal drug delivery Orlando, Fla volume:41 year:2016 pages:123-139 extent:17 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Skin segmentation Multi-manifold learning Feature space Voronoï segmentation |
| dewey-raw |
620 |
| isfreeaccess_bool |
false |
| container_title |
Propolis as lipid bioactive nano-carrier for topical nasal drug delivery |
| authorswithroles_txt_mv |
Hettiarachchi, R. @@aut@@ Peters, J.F. @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
ELV023814993 |
| dewey-sort |
3620 |
| id |
ELV035492554 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV035492554</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624022542.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jvcir.2016.09.011</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016018000023.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV035492554</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1047-3203(16)30201-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">620</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hettiarachchi, R.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">17</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Skin segmentation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Multi-manifold learning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Feature space Voronoï segmentation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Peters, J.F.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Academic Press</subfield><subfield code="a">Rassu, Giovanna ELSEVIER</subfield><subfield code="t">Propolis as lipid bioactive nano-carrier for topical nasal drug delivery</subfield><subfield code="d">2015</subfield><subfield code="g">Orlando, Fla</subfield><subfield code="w">(DE-627)ELV023814993</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:41</subfield><subfield code="g">year:2016</subfield><subfield code="g">pages:123-139</subfield><subfield code="g">extent:17</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jvcir.2016.09.011</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_50</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_72</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_136</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_162</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_176</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_181</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_203</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_227</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_352</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_676</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_791</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_1018</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">41</subfield><subfield code="j">2016</subfield><subfield code="h">123-139</subfield><subfield code="g">17</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">620</subfield></datafield></record></collection>
|
| author |
Hettiarachchi, R. |
| spellingShingle |
Hettiarachchi, R. ddc 620 ddc 540 Elsevier Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation |
| authorStr |
Hettiarachchi, R. |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV023814993 |
| format |
electronic Article |
| dewey-ones |
620 - Engineering & allied operations 540 - Chemistry & allied sciences |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
620 620 DE-600 540 VZ Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation Elsevier |
| topic |
ddc 620 ddc 540 Elsevier Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation |
| topic_unstemmed |
ddc 620 ddc 540 Elsevier Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation |
| topic_browse |
ddc 620 ddc 540 Elsevier Skin segmentation Elsevier Multi-manifold learning Elsevier Feature space Voronoï segmentation |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
j p jp |
| hierarchy_parent_title |
Propolis as lipid bioactive nano-carrier for topical nasal drug delivery |
| hierarchy_parent_id |
ELV023814993 |
| dewey-tens |
620 - Engineering 540 - Chemistry |
| hierarchy_top_title |
Propolis as lipid bioactive nano-carrier for topical nasal drug delivery |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV023814993 |
| title |
Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation |
| ctrlnum |
(DE-627)ELV035492554 (ELSEVIER)S1047-3203(16)30201-2 |
| title_full |
Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation |
| author_sort |
Hettiarachchi, R. |
| journal |
Propolis as lipid bioactive nano-carrier for topical nasal drug delivery |
| journalStr |
Propolis as lipid bioactive nano-carrier for topical nasal drug delivery |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology 500 - Science |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
zzz |
| container_start_page |
123 |
| author_browse |
Hettiarachchi, R. |
| container_volume |
41 |
| physical |
17 |
| class |
620 620 DE-600 540 VZ |
| format_se |
Elektronische Aufsätze |
| author-letter |
Hettiarachchi, R. |
| doi_str_mv |
10.1016/j.jvcir.2016.09.011 |
| dewey-full |
620 540 |
| title_sort |
multi-manifold-based skin classifier on feature space voronoï regions for skin segmentation |
| title_auth |
Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation |
| abstract |
• Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. |
| abstractGer |
• Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. |
| abstract_unstemmed |
• Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_50 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_136 GBV_ILN_162 GBV_ILN_165 GBV_ILN_176 GBV_ILN_181 GBV_ILN_203 GBV_ILN_227 GBV_ILN_352 GBV_ILN_676 GBV_ILN_791 GBV_ILN_1018 |
| title_short |
Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation |
| url |
https://doi.org/10.1016/j.jvcir.2016.09.011 |
| remote_bool |
true |
| author2 |
Peters, J.F. |
| author2Str |
Peters, J.F. |
| ppnlink |
ELV023814993 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth |
| doi_str |
10.1016/j.jvcir.2016.09.011 |
| up_date |
2024-07-06T17:42:05.498Z |
| _version_ |
1803852422052839424 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV035492554</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624022542.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jvcir.2016.09.011</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016018000023.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV035492554</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1047-3203(16)30201-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">620</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hettiarachchi, R.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multi-manifold-based skin classifier on feature space Voronoï regions for skin segmentation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">17</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• Voronoï-based image segmentation is proposed to segment skin candidate regions. • Multi-manifold-based classifier is proposed to improve skin classification accuracy. • Proposed skin classifier training data set is built with skin and skin-like classes. • Proposed method reduces the false positive rate of the skin classification process. • Proposed method gives the lowest minimal detection error compared to other methods.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Skin segmentation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Multi-manifold learning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Feature space Voronoï segmentation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Peters, J.F.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Academic Press</subfield><subfield code="a">Rassu, Giovanna ELSEVIER</subfield><subfield code="t">Propolis as lipid bioactive nano-carrier for topical nasal drug delivery</subfield><subfield code="d">2015</subfield><subfield code="g">Orlando, Fla</subfield><subfield code="w">(DE-627)ELV023814993</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:41</subfield><subfield code="g">year:2016</subfield><subfield code="g">pages:123-139</subfield><subfield code="g">extent:17</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jvcir.2016.09.011</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_50</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_72</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_136</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_162</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_176</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_181</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_203</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_227</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_352</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_676</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_791</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_1018</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">41</subfield><subfield code="j">2016</subfield><subfield code="h">123-139</subfield><subfield code="g">17</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">620</subfield></datafield></record></collection>
|
| score |
7.3997383 |