25 citations · 55 across the 22 of their papers we have counts for
3 papers · 1 filter
A semantics-driven methodology for high-quality image annotation
Fausto Giunchiglia, Mayukh Bagchi, Xiaolei Diao
Recent work in Machine Learning and Computer Vision has highlighted the presence of various types of systematic flaws inside ground truth object recognition benchmark datasets. Our…
Incremental Image Labeling via Iterative Refinement
Fausto Giunchiglia, Xiaolei Diao, Mayukh Bagchi
Data quality is critical for multimedia tasks, while various types of systematic flaws are found in image benchmark datasets, as discussed in recent work. In particular, the existe…
Object Recognition as Classification via Visual Properties
Fausto Giunchiglia, Mayukh Bagchi
We base our work on the teleosemantic modelling of concepts as abilities implementing the distinct functions of recognition and classification. Accordingly, we model two types of c…