9 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.CV2020★ 9 cited
OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold
Mohamed Yousef, Tom E. Bishop
Text recognition is a major computer vision task with a big set of associated challenges. One of those traditional challenges is the coupled nature of text recognition and segmenta…
cs.LG2020
Learning to hash with semantic similarity metrics and empirical KL divergence
Heikki Arponen, Tom E. Bishop
Learning to hash is an efficient paradigm for exact and approximate nearest neighbor search from massive databases. Binary hash codes are typically extracted from an image by round…
cs.IR2019
SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing
Heikki Arponen, Tom E Bishop
Using class labels to represent class similarity is a typical approach to training deep hashing systems for retrieval; samples from the same or different classes take binary 1 or 0…