Matches in SemOpenAlex for { <https://semopenalex.org/work/W2563442007> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W2563442007 abstract "Mammogram classification is directly related to computer-aided diagnosis of breast cancer. Traditional methods requires great effort to annotate the training data by costly manual labeling and specialized computational models to detect these annotations during test. Inspired by the success of using deep convolutional features for natural image analysis and multi-instance learning for labeling a set of instances/patches, we propose end-to-end trained deep multi-instance networks for mass classification based on whole mammogram without the aforementioned costly need to annotate the training data. We explore three different schemes to construct deep multi-instance networks for whole mammogram classification. Experimental results on the INbreast dataset demonstrate the robustness of proposed deep networks compared to previous work using segmentation and detection annotations in the training." @default.
- W2563442007 created "2017-01-06" @default.
- W2563442007 creator A5031854562 @default.
- W2563442007 creator A5077858309 @default.
- W2563442007 creator A5084618257 @default.
- W2563442007 creator A5090413637 @default.
- W2563442007 date "2016-12-18" @default.
- W2563442007 modified "2023-09-27" @default.
- W2563442007 title "Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification" @default.
- W2563442007 cites W1614900577 @default.
- W2563442007 cites W177004468 @default.
- W2563442007 cites W2110119381 @default.
- W2563442007 cites W2116288467 @default.
- W2563442007 cites W2155329254 @default.
- W2563442007 cites W2216351247 @default.
- W2563442007 cites W2344858100 @default.
- W2563442007 cites W2345010043 @default.
- W2563442007 cites W2493683088 @default.
- W2563442007 cites W2525205678 @default.
- W2563442007 cites W2527654160 @default.
- W2563442007 cites W2949362008 @default.
- W2563442007 cites W2950253601 @default.
- W2563442007 cites W2952587893 @default.
- W2563442007 cites W2964121744 @default.
- W2563442007 doi "https://doi.org/10.48550/arxiv.1612.05968" @default.
- W2563442007 hasPublicationYear "2016" @default.
- W2563442007 type Work @default.
- W2563442007 sameAs 2563442007 @default.
- W2563442007 citedByCount "2" @default.
- W2563442007 countsByYear W25634420072018 @default.
- W2563442007 countsByYear W25634420072019 @default.
- W2563442007 crossrefType "posted-content" @default.
- W2563442007 hasAuthorship W2563442007A5031854562 @default.
- W2563442007 hasAuthorship W2563442007A5077858309 @default.
- W2563442007 hasAuthorship W2563442007A5084618257 @default.
- W2563442007 hasAuthorship W2563442007A5090413637 @default.
- W2563442007 hasBestOaLocation W25634420071 @default.
- W2563442007 hasConcept C104317684 @default.
- W2563442007 hasConcept C108583219 @default.
- W2563442007 hasConcept C115961682 @default.
- W2563442007 hasConcept C119857082 @default.
- W2563442007 hasConcept C153180895 @default.
- W2563442007 hasConcept C154945302 @default.
- W2563442007 hasConcept C169903167 @default.
- W2563442007 hasConcept C185592680 @default.
- W2563442007 hasConcept C199360897 @default.
- W2563442007 hasConcept C2780801425 @default.
- W2563442007 hasConcept C41008148 @default.
- W2563442007 hasConcept C51632099 @default.
- W2563442007 hasConcept C55493867 @default.
- W2563442007 hasConcept C63479239 @default.
- W2563442007 hasConcept C75294576 @default.
- W2563442007 hasConcept C81363708 @default.
- W2563442007 hasConcept C89600930 @default.
- W2563442007 hasConceptScore W2563442007C104317684 @default.
- W2563442007 hasConceptScore W2563442007C108583219 @default.
- W2563442007 hasConceptScore W2563442007C115961682 @default.
- W2563442007 hasConceptScore W2563442007C119857082 @default.
- W2563442007 hasConceptScore W2563442007C153180895 @default.
- W2563442007 hasConceptScore W2563442007C154945302 @default.
- W2563442007 hasConceptScore W2563442007C169903167 @default.
- W2563442007 hasConceptScore W2563442007C185592680 @default.
- W2563442007 hasConceptScore W2563442007C199360897 @default.
- W2563442007 hasConceptScore W2563442007C2780801425 @default.
- W2563442007 hasConceptScore W2563442007C41008148 @default.
- W2563442007 hasConceptScore W2563442007C51632099 @default.
- W2563442007 hasConceptScore W2563442007C55493867 @default.
- W2563442007 hasConceptScore W2563442007C63479239 @default.
- W2563442007 hasConceptScore W2563442007C75294576 @default.
- W2563442007 hasConceptScore W2563442007C81363708 @default.
- W2563442007 hasConceptScore W2563442007C89600930 @default.
- W2563442007 hasLocation W25634420071 @default.
- W2563442007 hasLocation W25634420072 @default.
- W2563442007 hasLocation W25634420073 @default.
- W2563442007 hasOpenAccess W2563442007 @default.
- W2563442007 hasPrimaryLocation W25634420071 @default.
- W2563442007 hasRelatedWork W2337926734 @default.
- W2563442007 hasRelatedWork W2732542196 @default.
- W2563442007 hasRelatedWork W3012393889 @default.
- W2563442007 hasRelatedWork W3095523211 @default.
- W2563442007 hasRelatedWork W3099765033 @default.
- W2563442007 hasRelatedWork W3144574764 @default.
- W2563442007 hasRelatedWork W3156786002 @default.
- W2563442007 hasRelatedWork W4311257506 @default.
- W2563442007 hasRelatedWork W4313289428 @default.
- W2563442007 hasRelatedWork W564581980 @default.
- W2563442007 isParatext "false" @default.
- W2563442007 isRetracted "false" @default.
- W2563442007 magId "2563442007" @default.
- W2563442007 workType "article" @default.