1 citations · 1 across the 3 of their papers we have counts for
6 papers
Leveraging Unlabeled Data for Sketch-based Understanding
Javier Morales, Nils Murrugarra-Llerena, Jose M. Saavedra
Sketch-based understanding is a critical component of human cognitive learning and is a primitive communication means between humans. This topic has recently attracted the interest…
Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Image Retrieval
Anibal Fuentes, Jose M. Saavedra
Architectures based on siamese networks with triplet loss have shown outstanding performance on the image-based similarity search problem. This approach attempts to discriminate be…
Compact and Effective Representations for Sketch-based Image Retrieval
Pablo Torres, Jose M. Saavedra
Sketch-based image retrieval (SBIR) has undergone an increasing interest in the community of computer vision bringing high impact in real applications. For instance, SBIR brings an…
Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet
Andres Baloian, Nils Murrugarra-Llerena, Jose M. Saavedra
Visual attributes play an essential role in real applications based on image retrieval. For instance, the extraction of attributes from images allows an eCommerce search engine to…
A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition
Andre G. Hochuli, Alceu S. Britto, David A. Saji +3
Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby impos…
Pattern Spotting in Historical Documents Using Convolutional Models
Ignacio Úbeda, Jose M. Saavedra, Stéphane Nicolas +2
Pattern spotting consists of searching in a collection of historical document images for occurrences of a graphical object using an image query. Contrary to object detection, no pr…