Ghada Zamzmi (ed.) | Akateeminen Kirjakauppa

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MEDICAL IMAGE LEARNING WITH LIMITED AND NOISY DATA : FIRST INTERNATIONAL WORKSHOP, MILLAND 2022, HELD IN CONJUNCTION WITH MICCAI

Ghada Zamzmi (ed.); Sameer Antani (ed.); Ulas Bagci (ed.); Marius George Linguraru (ed.); Sivaramakrishnan Rajaraman (ed.)
Springer (2022)
Saatavuus: Tilaustuote
Pehmeäkantinen kirja

49,60 €

MEDICAL IMAGE LEARNING WITH LIMITED AND NOISY DATA : SECOND INTERNATIONAL WORKSHOP, MILLAND 2023, HELD IN CONJUNCTION WITH MICCA

Zhiyun Xue (ed.); Sameer Antani (ed.); Ghada Zamzmi (ed.); Feng Yang (ed.); Sivaramakrishnan Rajaraman (ed.); Sharon Huang
Springer (2023)
Saatavuus: Tilaustuote
Pehmeäkantinen kirja

107,50 €

Medical Image Learning with Limited and Noisy Data : First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI

Ghada Zamzmi (ed.), Sameer Antani (ed.), Ulas Bagci (ed.), Marius George Linguraru (ed.), Sivaramakrishnan Rajaraman (ed.)

49,60 €

Springer
Sivumäärä: 240 sivua
Asu: Pehmeäkantinen kirja
Julkaisuvuosi: 2022, 22.09.2022 (lisätietoa)
Kieli: Englanti

This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.

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