Search: WFRF:(Fredin Haslum Johan) >
What Makes Transfer...
-
Matsoukas, ChristosKTH,Beräkningsvetenskap och beräkningsteknik (CST),Stockholm, Sweden.;Sci Life Lab, Stockholm, Sweden.;AstraZeneca, Gothenburg, Sweden.
(author)
What Makes Transfer Learning Work for Medical Images : Feature Reuse & Other Factors
- Article/chapterEnglish2022
Publisher, publication year, extent ...
-
Institute of Electrical and Electronics Engineers (IEEE),2022
-
printrdacarrier
Numbers
-
LIBRIS-ID:oai:DiVA.org:kth-322794
-
https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-322794URI
-
https://doi.org/10.1109/CVPR52688.2022.00901DOI
Supplementary language notes
-
Language:English
-
Summary in:English
Part of subdatabase
Classification
-
Subject category:ref swepub-contenttype
-
Subject category:kon swepub-publicationtype
Notes
-
Part of proceedings ISBN 978-1-6654-6946-3QC 20230131
-
Transfer learning is a standard technique to transfer knowledge from one domain to another. For applications in medical imaging, transfer from ImageNet has become the de-facto approach, despite differences in the tasks and image characteristics between the domains. However, it is unclear what factors determine whether - and to what extent transfer learning to the medical domain is useful. The longstanding assumption that features from the source domain get reused has recently been called into question. Through a series of experiments on several medical image benchmark datasets, we explore the relationship between transfer learning, data size, the capacity and inductive bias of the model, as well as the distance between the source and target domain. Our findings suggest that transfer learning is beneficial in most cases, and we characterize the important role feature reuse plays in its success.
Subject headings and genre
Added entries (persons, corporate bodies, meetings, titles ...)
-
Fredin Haslum, JohanKTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab,AstraZeneca, Gothenburg, Sweden.(Swepub:kth)u13aplea
(author)
-
Sorkhei, MoeinKTH,Intelligenta system,Science for Life Laboratory, SciLifeLab(Swepub:kth)u1h9wx5m
(author)
-
Soderberg, MagnusAstraZeneca, Gothenburg, Sweden.
(author)
-
Smith, Kevin,1975-KTH,Science for Life Laboratory, SciLifeLab,Beräkningsvetenskap och beräkningsteknik (CST)(Swepub:kth)u1l33jpf
(author)
-
KTHBeräkningsvetenskap och beräkningsteknik (CST)
(creator_code:org_t)
Related titles
-
In:2022 IEEE/CVF conference on computer vision and pattern recognition (CVPR): Institute of Electrical and Electronics Engineers (IEEE), s. 9215-9224
Internet link
To the university's database