12 citations · 28 across the 7 of their papers we have counts for
5 papers
Learning Visual Models using a Knowledge Graph as a Trainer
Sebastian Monka, Lavdim Halilaj, Stefan Schmid +1
Traditional computer vision approaches, based on neural networks (NN), are typically trained on a large amount of image data. By minimizing the cross-entropy loss between a predict…
Towards Learning Cross-Modal Perception-Trace Models
Achim Rettinger, Viktoria Bogdanova, Philipp Niemann
Representation learning is a key element of state-of-the-art deep learning approaches. It enables to transform raw data into structured vector space embeddings. Such embeddings are…
Which Knowledge Graph Is Best for Me?
Michael Färber, Achim Rettinger
In recent years, DBpedia, Freebase, OpenCyc, Wikidata, and YAGO have been published as noteworthy large, cross-domain, and freely available knowledge graphs. Although extensively i…
Linking Tweets with Monolingual and Cross-Lingual News using Transformed Word Embeddings
Aditya Mogadala, Dominik Jung, Achim Rettinger
Social media platforms have grown into an important medium to spread information about an event published by the traditional media, such as news articles. Grouping such diverse sou…
Describing Natural Images Containing Novel Objects with Knowledge Guided Assitance
Aditya Mogadala, Umanga Bista, Lexing Xie +1
Images in the wild encapsulate rich knowledge about varied abstract concepts and cannot be sufficiently described with models built only using image-caption pairs containing select…