Matches in SemOpenAlex for { <https://semopenalex.org/work/W3087315877> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W3087315877 abstract "LSTMs have a proven track record in analyzing sequential data. But what about unordered instance bags, as found under a Multiple Instance Learning (MIL) setting? While not often used for this, we show LSTMs excell under this setting too. In addition, we show thatLSTMs are capable of indirectly capturing instance-level information us-ing only bag-level annotations. Thus, they can be used to learn instance-level models in a weakly supervised manner. Our empirical evaluation on both simplified (MNIST) and realistic (Lookbook and Histopathology) datasets shows that LSTMs are competitive with or even surpass state-of-the-art methods specially designed for handling specific MIL problems. Moreover, we show that their performance on instance-level prediction is close to that of fully-supervised methods." @default.
- W3087315877 created "2020-09-25" @default.
- W3087315877 creator A5055529222 @default.
- W3087315877 creator A5074816094 @default.
- W3087315877 creator A5077289752 @default.
- W3087315877 date "2019-09-11" @default.
- W3087315877 modified "2023-10-16" @default.
- W3087315877 title "In Defense of LSTMs for Addressing Multiple Instance Learning Problems" @default.
- W3087315877 cites W1485009520 @default.
- W3087315877 cites W1493597058 @default.
- W3087315877 cites W1686810756 @default.
- W3087315877 cites W2010792435 @default.
- W3087315877 cites W2029231546 @default.
- W3087315877 cites W2064675550 @default.
- W3087315877 cites W2112796928 @default.
- W3087315877 cites W2125479168 @default.
- W3087315877 cites W2126967273 @default.
- W3087315877 cites W2130942839 @default.
- W3087315877 cites W2131774270 @default.
- W3087315877 cites W2136848157 @default.
- W3087315877 cites W2137917285 @default.
- W3087315877 cites W2187089797 @default.
- W3087315877 cites W2193384753 @default.
- W3087315877 cites W2194775991 @default.
- W3087315877 cites W2307035320 @default.
- W3087315877 cites W2312404985 @default.
- W3087315877 cites W2313501142 @default.
- W3087315877 cites W2402268235 @default.
- W3087315877 cites W2424778531 @default.
- W3087315877 cites W2471768434 @default.
- W3087315877 cites W2510185399 @default.
- W3087315877 cites W2530887700 @default.
- W3087315877 cites W2531897166 @default.
- W3087315877 cites W2559833261 @default.
- W3087315877 cites W2560886373 @default.
- W3087315877 cites W2606783869 @default.
- W3087315877 cites W2753798143 @default.
- W3087315877 cites W2767520202 @default.
- W3087315877 cites W2785934082 @default.
- W3087315877 cites W2887997457 @default.
- W3087315877 cites W2898188206 @default.
- W3087315877 cites W2914010260 @default.
- W3087315877 cites W2949547296 @default.
- W3087315877 cites W2949611920 @default.
- W3087315877 cites W2950133940 @default.
- W3087315877 cites W2950527759 @default.
- W3087315877 cites W2953791858 @default.
- W3087315877 cites W2962690307 @default.
- W3087315877 cites W2963341956 @default.
- W3087315877 cites W2964303162 @default.
- W3087315877 cites W2973122905 @default.
- W3087315877 cites W3034472074 @default.
- W3087315877 cites W3099462466 @default.
- W3087315877 cites W3023071679 @default.
- W3087315877 doi "https://doi.org/10.48550/arxiv.1909.05690" @default.
- W3087315877 hasPublicationYear "2019" @default.
- W3087315877 type Work @default.
- W3087315877 sameAs 3087315877 @default.
- W3087315877 citedByCount "0" @default.
- W3087315877 crossrefType "posted-content" @default.
- W3087315877 hasAuthorship W3087315877A5055529222 @default.
- W3087315877 hasAuthorship W3087315877A5074816094 @default.
- W3087315877 hasAuthorship W3087315877A5077289752 @default.
- W3087315877 hasBestOaLocation W30873158771 @default.
- W3087315877 hasConcept C108583219 @default.
- W3087315877 hasConcept C11413529 @default.
- W3087315877 hasConcept C119857082 @default.
- W3087315877 hasConcept C154945302 @default.
- W3087315877 hasConcept C190502265 @default.
- W3087315877 hasConcept C41008148 @default.
- W3087315877 hasConcept C48103436 @default.
- W3087315877 hasConceptScore W3087315877C108583219 @default.
- W3087315877 hasConceptScore W3087315877C11413529 @default.
- W3087315877 hasConceptScore W3087315877C119857082 @default.
- W3087315877 hasConceptScore W3087315877C154945302 @default.
- W3087315877 hasConceptScore W3087315877C190502265 @default.
- W3087315877 hasConceptScore W3087315877C41008148 @default.
- W3087315877 hasConceptScore W3087315877C48103436 @default.
- W3087315877 hasLocation W30873158771 @default.
- W3087315877 hasOpenAccess W3087315877 @default.
- W3087315877 hasPrimaryLocation W30873158771 @default.
- W3087315877 hasRelatedWork W2787767549 @default.
- W3087315877 hasRelatedWork W2788522621 @default.
- W3087315877 hasRelatedWork W2791824431 @default.
- W3087315877 hasRelatedWork W2904174853 @default.
- W3087315877 hasRelatedWork W2905230381 @default.
- W3087315877 hasRelatedWork W2911822711 @default.
- W3087315877 hasRelatedWork W2963041618 @default.
- W3087315877 hasRelatedWork W2964030995 @default.
- W3087315877 hasRelatedWork W3092989768 @default.
- W3087315877 hasRelatedWork W3174189023 @default.
- W3087315877 isParatext "false" @default.
- W3087315877 isRetracted "false" @default.
- W3087315877 magId "3087315877" @default.
- W3087315877 workType "article" @default.