19 citations · 28 across the 5 of their papers we have counts for
5 papers
Boon: A Neural Search Engine for Cross-Modal Information Retrieval
Yan Gong, Georgina Cosma
Visual-Semantic Embedding (VSE) networks can help search engines better understand the meaning behind visual content and associate it with relevant textual information, leading to…
VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-Modal Information Retrieval
Yan Gong, Georgina Cosma, Axel Finke
The relations expressed in user queries are vital for cross-modal information retrieval. Relation-focused cross-modal retrieval aims to retrieve information that corresponds to the…
Multifaceted Hierarchical Report Identification for Non-Functional Bugs in Deep Learning Frameworks
Guoming Long, Tao Chen, Georgina Cosma
Non-functional bugs (e.g., performance- or accuracy-related bugs) in Deep Learning (DL) frameworks can lead to some of the most devastating consequences. Reporting those bugs on a…
Improving Visual-Semantic Embeddings by Learning Semantically-Enhanced Hard Negatives for Cross-modal Information Retrieval
Yan Gong, Georgina Cosma
Visual Semantic Embedding (VSE) aims to extract the semantics of images and their descriptions, and embed them into the same latent space for cross-modal information retrieval. Mos…
NatCSNN: A Convolutional Spiking Neural Network for recognition of objects extracted from natural images
Pedro Machado, Georgina Cosma, T. M McGinnity
Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and othe…