LEADER 04288oam 22007094 450 001 996199219303316 005 20230213224108.0 010 $a0-674-99045-5 035 $a(CKB)3820000000012082 035 $a(SSID)ssj0001370904 035 $a(PQKBManifestationID)12595187 035 $a(PQKBTitleCode)TC0001370904 035 $a(PQKBWorkID)11297590 035 $a(PQKB)10539643 035 $a(OCoLC)904378415 035 $a(MaCbHUP)hup0000141 035 $a(EXLCZ)993820000000012082 100 $a20141025d1914 my p 101 0 $aeng 135 $aurcn|||||| 181 $ctxt 182 $cc 183 $acr 200 10$aHeroides$eAmores /$fOvid ; with an English translation by Grant Showerman 205 $aNew edition /$brevised by G.P. Goold. 210 1$aCambridge, MA :$cHarvard University Press,$d2014. 215 $a1 online resource 225 1 $aLoeb Classical Library ; $v41 300 $aIncludes index. 327 $a1. Heroides; and, Amores. (2nd ed.) / with an English translation by Grant Showerman ; revised by G.P. Goold. -- 2. The art of love and other poems. (2nd ed.) / with an English translation by J.H. Mozley ; revised by G.P. Goold. -- 3. Metamorphoses 1. (3rd ed.) / with an English translation by Frank Justus Miller ; revised by G.P. Goold. -- 4. Metamorphoses 2. (2nd ed.) / with an English translation by Frank Justus Miller ; revised by G.P. Goold. -- 5. Fasti / with an English translation by James George Frazer ; revised by G.P. Goold. (2nd ed.) -- 6. Trista ex Ponto. (2nd ed.) / with an English translation by Arthur Leslie Wheeler ; revised by G.P. Goold. 330 $aIn Heroides, Ovid (43 BCE-17CE) allows legendary women to narrate their memories and express their emotions in verse letters to absent husbands and lovers. Ovid's Amores are three books of elegies ostensibly about the poet's love affair with his mistress Corinna.$bOvid (Publius Ovidius Naso, 43 BCE-17 CE), born at Sulmo, studied rhetoric and law at Rome. Later he did considerable public service there, and otherwise devoted himself to poetry and to society. Famous at first, he offended the emperor Augustus by his Ars Amatoria, and was banished because of this work and some other reason unknown to us, and dwelt in the cold and primitive town of Tomis on the Black Sea. He continued writing poetry, a kindly man, leading a temperate life. He died in exile. Ovid's main surviving works are the Metamorphoses, a source of inspiration to artists and poets including Chaucer and Shakespeare; the Fasti, a poetic treatment of the Roman year of which Ovid finished only half; the Amores, love poems; the Ars Amatoria, not moral but clever and in parts beautiful; Heroides, fictitious love letters by legendary women to absent husbands; and the dismal works written in exile: the Tristia, appeals to persons including his wife and also the emperor; and similar Epistulae ex Ponto. Poetry came naturally to Ovid, who at his best is lively, graphic and lucid. The Loeb Classical Library edition of Ovid is in six volumes. 606 $aLove poetry, Latin$xTranslations into English 606 $aLove poetry, Latin 606 $aWomen$vPoetry 606 $aElegiac poetry, Latin$3(OCoLC)907836$2fast 606 $aEpistolary poetry, Latin$3(OCoLC)914353$2fast 606 $aLove poetry, Latin$3(OCoLC)1002912$2fast 606 $aLove-letters$3(OCoLC)1003069$2fast 606 $aMan-woman relationships$3(OCoLC)1007080$2fast 606 $aMythology, Classical$3(OCoLC)1031758$2fast 606 $aWomen$3(OCoLC)1176568$2fast 615 0$aLove poetry, Latin$xTranslations into English. 615 0$aLove poetry, Latin. 615 0$aWomen 615 7$aElegiac poetry, Latin 615 7$aEpistolary poetry, Latin 615 7$aLove poetry, Latin 615 7$aLove-letters 615 7$aMan-woman relationships 615 7$aMythology, Classical 615 7$aWomen 676 $a871/.01 s 676 $a871/.01 700 $aOvid$f43 B.C.-17 A.D. or 18 A.D.,$0154954 702 $aGoold$b George Patrick$f1922-2001, 702 $aShowerman$b Grant$f1870-1935, 801 0$bMaCbHUP 801 2$bTLC 906 $aBOOK 912 $a996199219303316 996 $aHeroides$913345 997 $aUNISA LEADER 06693nam 22009495 450 001 996483157303316 005 20220721120300.0 010 $a3-031-08999-5 024 7 $a10.1007/978-3-031-08999-2 035 $a(CKB)5720000000019157 035 $a(DE-He213)978-3-031-08999-2 035 $a(MiAaPQ)EBC7048652 035 $a(Au-PeEL)EBL7048652 035 $a(OCoLC)1354205775 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/91300 035 $a(PPN)263897095 035 $a(EXLCZ)995720000000019157 100 $a20220721d2022 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBrainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries$b[electronic resource] $e7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I /$fedited by Alessandro Crimi, Spyridon Bakas 205 $a1st ed. 2022. 210 $aCham$cSpringer Nature$d2022 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v12962 311 $a3-031-08998-7 327 $aSupervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI. 330 $aThis two-volume set LNCS 12962 and 12963 constitutes the thoroughly refereed proceedings of the 7th International MICCAI Brainlesion Workshop, BrainLes 2021, as well as the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge, the Federated Tumor Segmentation (FeTS) Challenge, the Cross-Modality Domain Adaptation (CrossMoDA) Challenge, and the challenge on Quantification of Uncertainties in Biomedical Image Quantification (QUBIQ). These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in September 2021. The 91 revised papers presented in these volumes were selected form 151 submissions. Due to COVID-19 pandemic the conference was held virtually. This is an open access book. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v12962 606 $aComputer vision 606 $aArtificial intelligence 606 $aComputer engineering 606 $aComputer networks 606 $aApplication software 606 $aComputer Vision 606 $aArtificial Intelligence 606 $aComputer Engineering and Networks 606 $aComputer and Information Systems Applications 610 $aartificial intelligence 610 $abioinformatics 610 $acomputer science 610 $acomputer systems 610 $acomputer vision 610 $aeducation 610 $aimage analysis 610 $aimage processing 610 $aimage segmentation 610 $alearning 610 $amachine learning 610 $amedical images 610 $aneural networks 610 $apattern recognition 610 $asegmentation methods 610 $asoftware design 610 $asoftware engineering 610 $asoftware quality 610 $avalidation 610 $averification and validation 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aApplication software. 615 14$aComputer Vision. 615 24$aArtificial Intelligence. 615 24$aComputer Engineering and Networks. 615 24$aComputer and Information Systems Applications. 676 $a006.37 700 $aCrimi$b Alessandro$4edt$01354885 702 $aCrimi$b Alessandro$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBakas$b Spyridon$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996483157303316 996 $aBrainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries$93358588 997 $aUNISA LEADER 01095nam a22002771i 4500 001 991003696219707536 005 20040527133053.0 008 040802s1965 it |||||||||||||||||ita 035 $ab13113410-39ule_inst 035 $aARCHE-106602$9ExL 040 $aBiblioteca Interfacoltà$bita$cA.t.i. 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