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000 nam5i
001 2210080933799
003 DE-He213
005 20250321105247
007 cr nn 008mamaa
008 240228s2024 sz | s |||| 0|eng d
020 a97830315485749978-3-031-54857-4
024 a10.1007/978-3-031-54857-42doi
040 a221008
050 aQ334-342
050 aTA347.A78
072 aUYQ2bicssc
072 aCOM0040002bisacsh
072 aUYQ2thema
082 a006.3223
245 00 aMyopic Maculopathy Analysish[electronic resource] :bMICCAI Challenge MMAC 2023, Held in Conjunction with MICCAI 2023, Virtual Event, October 8–12, 2023, Proceedings /cedited by Bin Sheng, Hao Chen, Tien Yin Wong.
250 a1st ed. 2024.
264 aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.
300 aX, 121 p. 33 illus., 31 illus. in color.bonline resource.
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
347 atext filebPDF2rda
490 aLecture Notes in Computer Science,x1611-3349 ;v14563
505 aAutomated Detection of Myopic Maculopathy in MMAC 2023: Achievements in Classification, Segmentation, and Spherical Equivalent Prediction -- Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus Images -- Towards Label-efficient Deep Learning for Myopic Maculopathy Classification -- Ensemble Deep Learning Approaches for Myopic Maculopathy Plus Lesions Segmentation -- Beyond MobileNet: An improved MobileNet for Retinal Diseases -- Prediction of Spherical Equivalent With Vanilla ResNet -- Semi-supervised learning for Myopic Maculopathy Analysis -- A Clinically Guided Approach for Training Deep Neural Networks for Myopic Maculopathy Classification -- Classification of Myopic Maculopathy Images with Self-supervised Driven Multiple Instance Learning Network -- Self-supervised Learning and Data Diversity based Prediction of Spherical Equivalent -- Myopic Maculopathy Analysis using Multi-Task Learning and Pseudo Labeling.
520 aThis book constitutes the MICCAI Challenge, MMAC 2023, that held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, which took place in October 2023. The 11 long papers included in this volume presents a wide range of state-of-the-art deep learning methods developed for the various tasks presented in the challenge.
650 aArtificial intelligence.
650 aComputer vision.
650 aArtificial Intelligence.
650 aComputer Vision.
700 aSheng, Bin.eeditor.0(orcid)0000-0001-8678-27841https://orcid.org/0000-0001-8678-27844edt4http://id.loc.gov/vocabulary/relators/edt
700 aChen, Hao.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aWong, Tien Yin.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
710 aSpringerLink (Online service)
773 tSpringer Nature eBook
776 iPrinted edition:z9783031548567
776 iPrinted edition:z9783031548581
830 aLecture Notes in Computer Science,x1611-3349 ;v14563
856 uhttps://doi.org/10.1007/978-3-031-54857-4
912 aZDB-2-SCS
912 aZDB-2-SXCS
912 aZDB-2-LNC
950 aComputer Science (SpringerNature-11645)
950 aComputer Science (R0) (SpringerNature-43710)
Myopic Maculopathy Analysis[electronic resource] :MICCAI Challenge MMAC 2023, Held in Conjunction with MICCAI 2023, Virtual Event, October 8–12, 2023, Proceedings /edited by Bin Sheng, Hao Chen, Tien Yin Wong
Material type
전자책
Title
Myopic Maculopathy Analysis[electronic resource] :MICCAI Challenge MMAC 2023, Held in Conjunction with MICCAI 2023, Virtual Event, October 8–12, 2023, Proceedings /edited by Bin Sheng, Hao Chen, Tien Yin Wong
Author's Name
판 사항
1st ed. 2024.
Physical Description
X, 121 p 33 illus, 31 illus in color online resource.
Keyword
This book constitutes the MICCAI Challenge, MMAC 2023, that held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, which took place in October 2023. The 11 long papers included in this volume presents a wide range of state-of-the-art deep learning methods developed for the various tasks presented in the challenge.
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