Predicting gene and protein expression levels from DNA and protein sequences with Perceiver
Matteo Stefanini, Marta Lovino, Rita Cucchiara, Elisa Ficarra Journal: Computer Methods and Programs in Biomedicine (CMPB) March 2023 Abstract The functions of an organism and its biological processes result from the ex- pression of genes and proteins. Therefore quantifying and predicting mRNA and protein levels is a crucial aspect of scientific research. Concerning the prediction […]
CaMEL: Mean Teacher Learning for Image Captioning
Manuele Barraco, Matteo Stefanini, Marcella Cornia, Silvia Cascianelli, Lorenzo Baraldi, Rita Cucchiara Proceedings of the International Conference on Pattern Recognition (ICPR 2022) April 2022 Abstract Describing images in natural language is a fundamental step towards the automatic modeling of connections between the visual and textual modalities. In this paper we present CaMEL, a novel Transformer-based […]
Learning to Select:A Fully Attentive Approach for Novel Object Captioning
Marco Cagrandi, Marcella Cornia, Matteo Stefanini, Lorenzo Baraldi, Rita Cucchiara Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2021) June 2021 Abstract Image captioning models have lately shown impressive results when applied to standard datasets. Switching to real-life scenarios, however, constitutes a challenge due to the larger variety of visual concepts which are […]
Meshed-Memory Transformer for Image Captioning
Marcella Cornia, Matteo Stefanini, Lorenzo Baraldi, Rita Cucchiara Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) June 2020 Abstract Transformer-based architectures represent the state of the art in sequence modeling tasks like machine translation and language understanding. Their applicability to multi-modal contexts like image captioning, however, is still largely under-explored. […]