Electronic Resource

Deep Learning Approaches Applied to Image Classification of Renal Tumors: A Systematic Review

التفاصيل البيبلوغرافية
العنوان: Deep Learning Approaches Applied to Image Classification of Renal Tumors: A Systematic Review
المؤلفون: Pathologie Pathologen staf, Cancer, Pathologie Groep Van Diest, Amador, Sandra, Beuschlein, Felix, Chauhan, Vedant, Favier, Judith, Gil, David, Greenwood, Phillip, de Krijger, R. R., Kroiss, Matthias, Ortuño-Miquel, Samanta, Patocs, Attila, Stell, Anthony, Walch, Axel
بيانات النشر: Springer Netherlands 2024-03
نوع الوثيقة: Electronic Resource
URL: https://doi.org/10.1007/s11831-023-09995-w
http://hdl.handle.net/1874/451807
https://dspace.library.uu.nl/handle/1874/451807
http://www.scopus.com/inward/record.url?scp=85171305152&partnerID=8YFLogxK
1134-3060
Archives of Computational Methods in Engineering
31
2
615
622
الاتاحة: Open access content. Open access content
Open Access (free)
ملاحظة: English
Other Numbers: QGJ oai:dspace.library.uu.nl:1874/451807
Amador , S , Beuschlein , F , Chauhan , V , Favier , J , Gil , D , Greenwood , P , de Krijger , R R , Kroiss , M , Ortuño-Miquel , S , Patocs , A , Stell , A & Walch , A 2024 , ' Deep Learning Approaches Applied to Image Classification of Renal Tumors : A Systematic Review ' , Archives of Computational Methods in Engineering , vol. 31 , no. 2 , pp. 615-622 . https://doi.org/10.1007/s11831-023-09995-w
URN:NBN:NL:UI:10-1874-451807
364225211
1435902249
المصدر المساهم: UNIVERSITEIT UTRECHT
From OAIster®, provided by the OCLC Cooperative.
رقم الانضمام: edsoai.on1435902249
قاعدة البيانات: OAIster