Fiche du document
2020
- 20.500.13089/1dj0
Ce document est lié à :
https://hdl.handle.net/20.500.13089/1cho
Ce document est lié à :
https://doi.org/10.4000/books.aaccademia
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/isbn/979-12-80136-32-9
info:eu-repo/semantics/openAccess , https://creativecommons.org/licenses/by-nc-nd/4.0/
Sujets proches
Parliamentary government Representation Self-government Political representation Pea, Pigeon Pea, Catjang Catjang Angola pea Pea, No-eye Cajanus indicus Cajanus cajan Congo pea Dal Cajan pea Pea, Congo Congo bean Red gram Cajanus flavus Pea, Angola Catjang pea No-eye pea Bean, Congo Arhar Cytisus cajan Pigeonpea Cajan Cajanus bicolor Dhal Pea, Cajan Gram, Red Papers Livestock rations Rations, Livestock Domestic animals--Feeding and feeds Animal rations Feeding stuffs Livestock--Feeding and feeds Feedingstuff Feed Animal feeds Rations, Animal Feeding and feeding stuffs Animals--Feeding and feeds Fodder Feedstuff Competition (Economics) Economic competition Competitiveness (Economics)Citer ce document
Stefano Fiorucci, « SNK @ DANKMEMES: Leveraging Pretrained Embeddings for Multimodal Meme Detection », Accademia University Press
Partage / Export
Résumé
In this paper, we describe and present the results of meme detection system, specifically developed and submitted for our participation to the first subtask of DANKMEMES (EVALITA 2020). We built simple classifiers, consisting in feed forward neural networks. They leverage existing pretrained embeddings, both for text and image representation. Our best system (SNK1) achieves good results in meme detection (F1 = 0.8473), ranking 2nd in the competition, at a distance of 0.0028 from the first classified.
