18 citations · 19 across the 3 of their papers we have counts for
6 papers
Deep learning for structural health monitoring: An application to heritage structures
Fabio Carrara, Fabrizio Falchi, Maria Girardi +3
Thanks to recent advancements in numerical methods, computer power, and monitoring technology, seismic ambient noise provides precious information about the structural behavior of…
Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features
Nicola Messina, Giuseppe Amato, Fabrizio Falchi +2
Cross-modal retrieval is an important functionality in modern search engines, as it increases the user experience by allowing queries and retrieved objects to pertain to different…
Solving the Same-Different Task with Convolutional Neural Networks
Nicola Messina, Giuseppe Amato, Fabio Carrara +2
Deep learning demonstrated major abilities in solving many kinds of different real-world problems in computer vision literature. However, they are still strained by simple reasonin…
Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders
Nicola Messina, Giuseppe Amato, Andrea Esuli +3
Despite the evolution of deep-learning-based visual-textual processing systems, precise multi-modal matching remains a challenging task. In this work, we tackle the task of cross-m…
Transformer Reasoning Network for Image-Text Matching and Retrieval
Nicola Messina, Fabrizio Falchi, Andrea Esuli +1
Image-text matching is an interesting and fascinating task in modern AI research. Despite the evolution of deep-learning-based image and text processing systems, multi-modal matchi…
Virtual to Real adaptation of Pedestrian Detectors
Luca Ciampi, Nicola Messina, Fabrizio Falchi +2
Pedestrian detection through Computer Vision is a building block for a multitude of applications. Recently, there was an increasing interest in Convolutional Neural Network-based a…