Name
Title | ||
|---|---|---|
Referring expression generation from images via deep learning object extraction and fuzzy graphs |
Abstract | ||
|---|---|---|
We propose an approach to obtain referring expressions for objects in images. Segmentation and categorization is performed via deep learning, providing the basis for a graph-based representation of the context that is later enriched with fuzzy properties. Referable objects and their corresponding expressions are obtained from the graph using extraction algorithms following a classical REG approach. The proposal is more flexible and scalable than end-to-end deep learning techniques. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/FUZZ45933.2021.9494544 | 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) |
Keywords | DocType | ISSN |
Referring expression generation,deep learning,fuzzy graphs,computer vision,representation by levels | Conference | 1544-5615 |
ISBN | Citations | PageRank |
978-1-6654-4408-8 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jesús Chamorro-Martínez | 1 | 0 | 0.34 |
| N. Marín | 2 | 0 | 0.34 |
| Míriam Mengíbar-Rodríguez | 3 | 0 | 0.34 |
| Gustavo Rivas-Gervilla | 4 | 1 | 2.39 |
| Daniel Sánchez | 5 | 124 | 15.47 |