cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4275240
title: Tunizi: Tunisian Arabizi Sentiment Analysis Dataset

description: Tunizi is the first 100% Tunisian Arabizi sentiment analysis dataset. Tunisian Arabizi is the representation of the tunisian dialect written in Latin characters and numbers rather than Arabic letters.We gathered comments from social media platforms that express sentiment about popular topics. For this purpose, we extracted 100k comments using public streaming APIs. Tunizi was preprocessed by removing links, emoji symbols, and punctuations. The collected comments were manually annotated using an overall polarity: positive (1), negative (-1) and neutral (0) class. We divided the dataset into separate training, validation and test sets, with a ratio of 7:1:2 with a balanced split where the number of comments from positive class and negative class are almost the same.
description: This dataset contains comments written in Tunisian Arabizi which represents the Tunisian dialect written in Latin letters and numbers.
DOI: 10.5281/zenodo.4271535
title: Tunizi: Tunisian Arabizi Sentiment Analysis Dataset

description: Tunizi is the first 100% Tunisian Arabizi sentiment analysis dataset. Tunisian Arabizi is the representation of the tunisian dialect written in Latin characters and numbers rather than Arabic letters.We gathered comments from social media platforms that express sentiment about popular topics. For this purpose, we extracted 100k comments using public streaming APIs. Tunizi was preprocessed by removing links, emoji symbols, and punctuations. The collected comments were manually annotated using an overall polarity: positive (1), negative (-1) and neutral (0) class. We divided the dataset into separate training, validation and test sets, with a ratio of 7:1:2 with a balanced split where the number of comments from positive class and negative class are almost the same.
description: This dataset contains comments written in Tunisian Arabizi which represents the Tunisian dialect written in Latin letters and numbers.
DOI: 10.14272/gyfsyevkfoolfz-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (17-methoxy-5,7-dioxa-13-azoniapentacyclo[11.8.0.02,10.04,8.015,20]henicosa-1(13),2,4(8),9,14,16,18,20-octaen-16-ol;chloride)
title: InChI=1S/C19H15NO4.ClH/c1-22-16-3-2-11-6-15-13-8-18-17(23-10-24-18)7-12(13)4-5-20(15)9-14(11)19(16)21;/h2-3,6-9H,4-5,10H2,1H3;1H

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ 9.07 (s, 1H), 7.98 (s, 1H), 7.61 (s, 1H), 7.21 (d, J = 7.8 Hz, 1H), 6.96 (s, 1H), 6.35 (d, J = 7.8 Hz, 1H), 6.09 (s, 2H), 4.48 (t, J = 6.1 Hz, 2H), 3.72 (s, 3H), 3.04 (t, J = 6.1 Hz, 2H).Impurities: 9% DMFMissing Signal (1H, OH) due to H/D exchange in DMSO-d6.
DOI: 10.14272/gyfsyevkfoolfz-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (17-methoxy-5,7-dioxa-13-azoniapentacyclo[11.8.0.02,10.04,8.015,20]henicosa-1(13),2,4(8),9,14,16,18,20-octaen-16-ol;chloride)
title: InChI=1S/C19H15NO4.ClH/c1-22-16-3-2-11-6-15-13-8-18-17(23-10-24-18)7-12(13)4-5-20(15)9-14(11)19(16)21;/h2-3,6-9H,4-5,10H2,1H3;1H

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, DMSO-d6, ppm) δ 167.5, 150.1, 148.8, 147.7, 146.2, 133.7, 132.5, 129.7, 122.3, 121.7, 120.4, 117.6, 108.7, 105.2, 102.0, 101.3, 56.1, 52.8, 28.0.
DOI: 10.14272/plpzwdlhcmcacf-uhfffaoysa-m.1
title: cucurbit[7]uril-HEG-berberine conjugate
title: InChI=1S/C76H83N32O24.BrH/c1-123-45-3-2-39-18-44-42-20-47-46(130-38-131-47)19-40(42)4-5-79(44)22-43(39)48(45)129-17-16-128-15-14-127-13-12-126-11-10-125-9-8-124-7-6-80-21-41(77-78-80)23-132-76-61-105-34-101-58-57-97(70(101)117)30-93-54-53-89(66(93)113)26-85-50-49-81(62(85)109)24-83-51-52-87(64(83)111)28-91-55-56-95(68(91)115)32-99-59-60(103(72(99)119)36-107(76)74(105)121)104-37-108(76)75(122)106(61)35-102(58)71(118)98(57)31-94(54)67(114)90(53)27-86(50)63(110)82(49)25-84(51)65(112)88(52)29-92(55)69(116)96(56)33-100(59)73(104)120;/h2-3,18-22,49-61H,4-17,23-38H2,1H3;1H/q+1;/p-1

description: This dataset contains experimental data from a sample (InChI=1S/C76H83N32O24.BrH/c1-123-45-3-2-39-18-44-42-20-47-46(130-38-131-47)19-40(42)4-5-79(44)22-43(39)48(45)129-17-16-128-15-14-127-13-12-126-11-10-125-9-8-124-7-6-80-21-41(77-78-80)23-132-76-61-105-34-101-58-57-97(70(101)117)30-93-54-53-89(66(93)113)26-85-50-49-81(62(85)109)24-83-51-52-87(64(83)111)28-91-55-56-95(68(91)115)32-99-59-60(103(72(99)119)36-107(76)74(105)121)104-37-108(76)75(122)106(61)35-102(58)71(118)98(57)31-94(54)67(114)90(53)27-86(50)63(110)82(49)25-84(51)65(112)88(52)29-92(55)69(116)96(56)33-100(59)73(104)120;/h2-3,18-22,49-61H,4-17,23-38H2,1H3;1H/q+1;/p-1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/plpzwdlhcmcacf-uhfffaoysa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C76H83N32O24.BrH/c1-123-45-3-2-39-18-44-42-20-47-46(130-38-131-47)19-40(42)4-5-79(44)22-43(39)48(45)129-17-16-128-15-14-127-13-12-126-11-10-125-9-8-124-7-6-80-21-41(77-78-80)23-132-76-61-105-34-101-58-57-97(70(101)117)30-93-54-53-89(66(93)113)26-85-50-49-81(62(85)109)24-83-51-52-87(64(83)111)28-91-55-56-95(68(91)115)32-99-59-60(103(72(99)119)36-107(76)74(105)121)104-37-108(76)75(122)106(61)35-102(58)71(118)98(57)31-94(54)67(114)90(53)27-86(50)63(110)82(49)25-84(51)65(112)88(52)29-92(55)69(116)96(56)33-100(59)73(104)120;/h2-3,18-22,49-61H,4-17,23-38H2,1H3;1H/q+1;/p-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, D2O, ppm) δ 9.55 (s, 1H), 9.05 (s, 1H), 8.40 (d, J = 9.2 Hz, 1H), 8.10 (s, 1H), 8.04 (d, J = 9.3 Hz, 1H), 6.65 (s, 1H), 5.79-5.38 (m, 31H), 4.66-4.56 (m, 13H), 4.27-3.42 (m, 33H).due to the complex structure, the total amount of protons could not be confirmed by a clear assignment
DOI: 10.14272/lacskpodwqxgsb-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (1-[2-(2-bromoethoxy)ethoxy]-2-[2-[2-(2-bromoethoxy)ethoxy]ethoxy]ethane)
title: InChI=1S/C12H24Br2O5/c13-1-3-15-5-7-17-9-11-19-12-10-18-8-6-16-4-2-14/h1-12H2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, CDCl3, ppm) δ = 3.81 (t, J = 3.2 Hz, 4H), 3.66 (m, 16H), 3.47 (t, J = 3.2 Hz, 4H). Impurities: 6% ethyl acetate, 10% hexane, unknown impurities at 2.77 ppm.
DOI: 10.14272/lacskpodwqxgsb-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (1-[2-(2-bromoethoxy)ethoxy]-2-[2-[2-(2-bromoethoxy)ethoxy]ethoxy]ethane)
title: InChI=1S/C12H24Br2O5/c13-1-3-15-5-7-17-9-11-19-12-10-18-8-6-16-4-2-14/h1-12H2

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, CDCl3, ppm) δ = 71.4 (2C), 70.8 (2C), 70.8 (4C), 70.7 (2C), 30.5 (2C). Impurities: ethyl acetate, hexane.
DOI: 10.6084/m9.figshare.11400960.v1
title: Stimulation of adventitious root formation by the oligosaccharin OSRG at the transcriptome level

description: Oligosaccharins, which are biologically active oligosaccharide fragments of cell wall polysaccharides, may regulate the processes of growth and development as well as the response to stress factors. We characterized the effect of the oligosaccharin that stimulates rhizogenesis (OSRG) on the gene expression profile in the course of IAA-induced formation of adventitious roots in hypocotyl explants of buckwheat (<i>Fagopyrum esculentum</i> Moench.). The transcriptomes at two stages of IAA-induced root primordium formation (6 h and 24 h after induction) were compared after either treatment with auxin alone or joint treatment with auxin and OSRG. The set of differentially expressed genes indicated the special importance of oligosaccharin at the early stage of auxin-induced adventitious root formation. The list of genes with altered mRNA abundance in the presence of oligosaccharin included those, which <i>Arabidopsis</i> homologs encode proteins directly involved in the response to auxin as well as proteins that contribute to redox regulation, detoxification of various compounds, vesicle trafficking, and cell wall modification. The obtained results contribute to understanding the mechanism of adventitious root formation and demonstrate that OSRG is involved in fine-tuning of ROS and auxin regulatory modes involved in root development.
DOI: 10.6084/m9.figshare.11400960
title: Stimulation of adventitious root formation by the oligosaccharin OSRG at the transcriptome level

description: Oligosaccharins, which are biologically active oligosaccharide fragments of cell wall polysaccharides, may regulate the processes of growth and development as well as the response to stress factors. We characterized the effect of the oligosaccharin that stimulates rhizogenesis (OSRG) on the gene expression profile in the course of IAA-induced formation of adventitious roots in hypocotyl explants of buckwheat (<i>Fagopyrum esculentum</i> Moench.). The transcriptomes at two stages of IAA-induced root primordium formation (6 h and 24 h after induction) were compared after either treatment with auxin alone or joint treatment with auxin and OSRG. The set of differentially expressed genes indicated the special importance of oligosaccharin at the early stage of auxin-induced adventitious root formation. The list of genes with altered mRNA abundance in the presence of oligosaccharin included those, which <i>Arabidopsis</i> homologs encode proteins directly involved in the response to auxin as well as proteins that contribute to redox regulation, detoxification of various compounds, vesicle trafficking, and cell wall modification. The obtained results contribute to understanding the mechanism of adventitious root formation and demonstrate that OSRG is involved in fine-tuning of ROS and auxin regulatory modes involved in root development.
DOI: 10.14272/ijfmwhwxebuokr-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (1-(2-bromoethoxy)-2-[2-(2-bromoethoxy)ethoxy]ethane)
title: InChI=1S/C8H16Br2O3/c9-1-3-11-5-7-13-8-6-12-4-2-10/h1-8H2

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, CDCl3, ppm) δ = 71.2 (2C), 70.7 (2C), 70.6 (2C), 30.4 (2C).
DOI: 10.21258/1470549
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897258
DOI: 10.14272/ijfmwhwxebuokr-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (1-(2-bromoethoxy)-2-[2-(2-bromoethoxy)ethoxy]ethane)
title: InChI=1S/C8H16Br2O3/c9-1-3-11-5-7-13-8-6-12-4-2-10/h1-8H2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, CDCl3, ppm) δ = 3.82 (t, J = 3.2 Hz, 4H), 3.68 (s, 8H), 3.48 (t, J = 3.2 Hz, 4H). Impurities: 1% HMDSO at 0.07 ppm.
DOI: 10.14272/ijfmwhwxebuokr-uhfffaoysa-n.1
title: 1-(2-bromoethoxy)-2-[2-(2-bromoethoxy)ethoxy]ethane
title: InChI=1S/C8H16Br2O3/c9-1-3-11-5-7-13-8-6-12-4-2-10/h1-8H2

description: This dataset contains experimental data from a sample (1-(2-bromoethoxy)-2-[2-(2-bromoethoxy)ethoxy]ethane, InChI=1S/C8H16Br2O3/c9-1-3-11-5-7-13-8-6-12-4-2-10/h1-8H2). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR)
DOI: 10.14272/sccuvbvhkklhod-uhfffaoysa-m.1
title: cucurbit[7]uril-TEG-berberine conjugate
title: InChI=1S/C72H75N32O22.BrH/c1-119-41-3-2-35-14-40-38-16-43-42(124-34-125-43)15-36(38)4-5-75(40)18-39(35)44(41)123-13-12-122-11-10-121-9-8-120-7-6-76-17-37(73-74-76)19-126-72-57-101-30-97-54-53-93(66(97)113)26-89-50-49-85(62(89)109)22-81-46-45-77(58(81)105)20-79-47-48-83(60(79)107)24-87-51-52-91(64(87)111)28-95-55-56(99(68(95)115)32-103(72)70(101)117)100-33-104(72)71(118)102(57)31-98(54)67(114)94(53)27-90(50)63(110)86(49)23-82(46)59(106)78(45)21-80(47)61(108)84(48)25-88(51)65(112)92(52)29-96(55)69(100)116;/h2-3,14-18,45-57H,4-13,19-34H2,1H3;1H/q+1;/p-1

description: This dataset contains experimental data from a sample (InChI=1S/C72H75N32O22.BrH/c1-119-41-3-2-35-14-40-38-16-43-42(124-34-125-43)15-36(38)4-5-75(40)18-39(35)44(41)123-13-12-122-11-10-121-9-8-120-7-6-76-17-37(73-74-76)19-126-72-57-101-30-97-54-53-93(66(97)113)26-89-50-49-85(62(89)109)22-81-46-45-77(58(81)105)20-79-47-48-83(60(79)107)24-87-51-52-91(64(87)111)28-95-55-56(99(68(95)115)32-103(72)70(101)117)100-33-104(72)71(118)102(57)31-98(54)67(114)94(53)27-90(50)63(110)86(49)23-82(46)59(106)78(45)21-80(47)61(108)84(48)25-88(51)65(112)92(52)29-96(55)69(100)116;/h2-3,14-18,45-57H,4-13,19-34H2,1H3;1H/q+1;/p-1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/sccuvbvhkklhod-uhfffaoysa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C72H75N32O22.BrH/c1-119-41-3-2-35-14-40-38-16-43-42(124-34-125-43)15-36(38)4-5-75(40)18-39(35)44(41)123-13-12-122-11-10-121-9-8-120-7-6-76-17-37(73-74-76)19-126-72-57-101-30-97-54-53-93(66(97)113)26-89-50-49-85(62(89)109)22-81-46-45-77(58(81)105)20-79-47-48-83(60(79)107)24-87-51-52-91(64(87)111)28-95-55-56(99(68(95)115)32-103(72)70(101)117)100-33-104(72)71(118)102(57)31-98(54)67(114)94(53)27-90(50)63(110)86(49)23-82(46)59(106)78(45)21-80(47)61(108)84(48)25-88(51)65(112)92(52)29-96(55)69(100)116;/h2-3,14-18,45-57H,4-13,19-34H2,1H3;1H/q+1;/p-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, D2O, ppm) δ 9.53 (s, 1H), 9.07 (s, 1H), 8.39 (d, J = 9.1 Hz, 1H), 8.04 (d, J = 9.3 Hz, 1H), 6.63 (s, 1H), 5.83-5.27 (m, 31H), 4.62-4.55 (m, 14H), 4.27-3.70 (m, 25H).due to the complex structure, the total amount of protons could not be confirmed by a clear assignment
DOI: 10.21258/1467675
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899264
DOI: 10.14272/fixmwogokffcen-uhfffaoysa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C31H39N4O9.BrH/c1-36-28-3-2-23-18-27-25-20-30-29(43-22-44-30)19-24(25)4-6-35(27)21-26(23)31(28)42-17-16-41-15-14-40-13-12-39-11-10-38-9-8-37-7-5-33-34-32;/h2-3,18-21H,4-17,22H2,1H3;1H/q+1;/p-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, D2O, ppm) δ 9.60 (s, 1H), 8.29 (s, 1H), 7.94 (d, J = 8.7 Hz, 1H), 7.82 (s, J = 8.9 Hz, 1H), 7.30 (s, 1H), 6.90 (s, 1H), 6.06 (s, 2H), 4.84 (t, J = 6.0 Hz, 2H), 4.49 (t, J = 3.1 Hz, 2H), 4.02 (s, 3H), 3.92 (t, J = 3.1 Hz, 2H), 3.72 (t, J = 3.5 Hz, 2H), 3.65–3.58 (m, 16H), 3.41 (t, J = 4.3 Hz, 2H), 3.20 (t, J = 6.0 Hz, 2H).
DOI: 10.14272/fixmwogokffcen-uhfffaoysa-m.1
title: C31H39BrN4O9
title: InChI=1S/C31H39N4O9.BrH/c1-36-28-3-2-23-18-27-25-20-30-29(43-22-44-30)19-24(25)4-6-35(27)21-26(23)31(28)42-17-16-41-15-14-40-13-12-39-11-10-38-9-8-37-7-5-33-34-32;/h2-3,18-21H,4-17,22H2,1H3;1H/q+1;/p-1

description: This dataset contains experimental data from a sample (InChI=1S/C31H39N4O9.BrH/c1-36-28-3-2-23-18-27-25-20-30-29(43-22-44-30)19-24(25)4-6-35(27)21-26(23)31(28)42-17-16-41-15-14-40-13-12-39-11-10-38-9-8-37-7-5-33-34-32;/h2-3,18-21H,4-17,22H2,1H3;1H/q+1;/p-1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR)
DOI: 10.14272/fixmwogokffcen-uhfffaoysa-m/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C31H39N4O9.BrH/c1-36-28-3-2-23-18-27-25-20-30-29(43-22-44-30)19-24(25)4-6-35(27)21-26(23)31(28)42-17-16-41-15-14-40-13-12-39-11-10-38-9-8-37-7-5-33-34-32;/h2-3,18-21H,4-17,22H2,1H3;1H/q+1;/p-1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, D2O, ppm) δ 151.8, 150.6, 150.1, 147.7, 144.3, 141.9, 137.6, 133.2, 130.2, 126.3, 123.9, 121.9, 119.9, 108.4, 104.9, 102.3, 72.9, 69.8, 69.6, 69.5, 69.5, 69.5, 69.5, 69.4, 69.4, 69.3, 69.2, 56.6, 56.0, 50.1, 26.7.
DOI: 10.21258/1462549
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897693
DOI: 10.14272/ulnwezyjtnmiqq-uhfffaoysa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (4-[(E)-2-[1-(1-adamantyl)pyridin-1-ium-4-yl]ethenyl]-N,N-dimethylaniline;bromide)
title: InChI=1S/C25H31N2.BrH/c1-26(2)24-7-5-19(6-8-24)3-4-20-9-11-27(12-10-20)25-16-21-13-22(17-25)15-23(14-21)18-25;/h3-12,21-23H,13-18H2,1-2H3;1H/q+1;/p-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, MeOH-d3, ppm) δ = 8.85 (d, J = 7.0 Hz, 2H), 7.98 (d, J = 6.3 Hz, 2H), 7.85 (d, J = 15.8 Hz, 1H), 7.62 (d, J = 8.1 Hz, 2H), 7.10 (d, J = 15.9 Hz, 1H), 6.79 (d, J = 7.4 Hz, 2H), 3.07 (s, 6H), 2.42–2.22 (m, 9H), 1.87 (s, 6H).
DOI: 10.14272/ulnwezyjtnmiqq-uhfffaoysa-m/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (4-[(E)-2-[1-(1-adamantyl)pyridin-1-ium-4-yl]ethenyl]-N,N-dimethylaniline;bromide)
title: InChI=1S/C25H31N2.BrH/c1-26(2)24-7-5-19(6-8-24)3-4-20-9-11-27(12-10-20)25-16-21-13-22(17-25)15-23(14-21)18-25;/h3-12,21-23H,13-18H2,1-2H3;1H/q+1;/p-1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, MeOH-d3, ppm) δ =155.9, 154.0, 144.4, 141.0 (2C), 131.6 (2C), 124.2, 123.6 (2C), 117.6, 113.1 (2C), 68.7, 43.0 (3C), 40.2 (2C), 36.2 (3C), 31.6 (3C).
DOI: 10.21258/1444523
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897226
DOI: 10.21258/1463499
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899460
DOI: 10.21258/1437423
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902151
DOI: 10.21258/1450343
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899340
DOI: 10.21258/1453493
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902289
DOI: 10.21258/1456408
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899202
DOI: 10.21258/1442141
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902176
DOI: 10.21258/1450777
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899474
DOI: 10.21258/1442043
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897365
DOI: 10.21258/1459675
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902103
DOI: 10.21258/1467466
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899496
DOI: 10.21258/1475949
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897668
DOI: 10.21258/1466173
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898341
DOI: 10.21258/1462976
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899505
DOI: 10.21258/1455030
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899670
DOI: 10.21258/1446284
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899084
DOI: 10.21258/1473430
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902119
DOI: 10.5519/qd.5gcimnir
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (307 records)
DOI: 10.21258/1474702
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897613
DOI: 10.21258/1444582
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899322
DOI: 10.21258/1446772
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902085
DOI: 10.21258/1435514
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 896907
DOI: 10.21258/1451637
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897630
DOI: 10.21258/1464588
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899544
DOI: 10.21258/1467004
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899473
DOI: 10.21258/1452103
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902261
DOI: 10.21258/1462429
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898957
DOI: 10.21258/1460158
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897316
DOI: 10.21258/1463398
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897283
DOI: 10.21258/1435910
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897459
DOI: 10.21258/1446836
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898149
DOI: 10.21227/k4rv-ht08
title: SEG-FOOD-Semantic Food Segmentation Through Deep Learning

description: Semantic segmentation is the topic of interest among deep learning researchers in the recent era. It has many applications in different domains including, food recognition. In the case of food recognition, it removes the non-food background from the food portion. There is no large public food dataset available to train semantic segmentation models. We prepared a dataset named ’SEG-FOOD’[44] containing images of FOOD101, PFID, and Pakistani Food dataset and open-sourced the annotated dataset for future research. We annotated the images using JS Segment annotator. For experimentation, please refer to our paper, and for the starter code, please refer to our Github repository.* Please note that our main contribution is a manual annotation by JS-Segment so that researchers can explore various semantic segmentation based methods based on deep learning. The images of this dataset contain images from Food101, PFID dataset, and our own collected dataset of Pakistani Food.
DOI: 10.21227/g87x-5c64
title: SEG-FOOD-Semantic Food Segmentation Through Deep Learning

description: Semantic segmentation is the topic of interest among deep learning researchers in the recent era. It has many applications in different domains including, food recognition. In the case of food recognition, it removes the non-food background from the food portion. There is no large public food dataset available to train semantic segmentation models. We prepared a dataset named ’SEG-FOOD’[44] containing images of FOOD101, PFID, and Pakistani Food dataset and open-sourced the annotated dataset for future research. We annotated the images using JS Segment annotator. For experimentation, please refer to our paper, and for the starter code, please refer to our Github repository.* Please note that our main contribution is a manual annotation by JS-Segment so that researchers can explore various semantic segmentation based methods based on deep learning. The images of this dataset contain images from Food101, PFID dataset, and our own collected dataset of Pakistani Food.
DOI: 10.21258/1435418
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899402
DOI: 10.21258/1439728
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899624
DOI: 10.21227/08z6-5a49
title: SEG-FOOD-Semantic Food Segmentation Through Deep Learning

description: Semantic segmentation is the topic of interest among deep learning researchers in the recent era. It has many applications in different domains including, food recognition. In the case of food recognition, it removes the non-food background from the food portion. There is no large public food dataset available to train semantic segmentation models. We prepared a dataset named ’SEG-FOOD’[44] containing images of FOOD101, PFID, and Pakistani Food dataset and open-sourced the annotated dataset for future research. We annotated the images using JS Segment annotator. For experimentation, please refer to our paper, and for the starter code, please refer to our Github repository.* Please note that our main contribution is a manual annotation by JS-Segment so that researchers can explore various semantic segmentation based methods based on deep learning. The images of this dataset contain images from Food101, PFID dataset, and our own collected dataset of Pakistani Food.
DOI: 10.6084/m9.figshare.13352303
title: SW_F_1_1.fq.gz

description: SW-S: male sterility mutant; SW-F: fertile plant . Each sample sequence repeat 3 times，eg. SW_F_1, SW_F_2, SW_F_3. bi-directional sequencing，eg.SW_F_1_1, and SW_F_1_2
DOI: 10.6084/m9.figshare.13352303.v1
title: SW_F_1_1.fq.gz

description: SW-S: male sterility mutant; SW-F: fertile plant . Each sample sequence repeat 3 times，eg. SW_F_1, SW_F_2, SW_F_3. bi-directional sequencing，eg.SW_F_1_1, and SW_F_1_2
DOI: 10.21258/1444761
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899321