| PROJECT: | Compression of Multimodal Biomedical Images using Neural Networks | |||||
| ACRONYM: | CoMBINNe | |||||
| MAIN OBJECTIVE: | The main goals of this research plan are: (i) to investigate and propose new prediction modes to increase the multimodal compression efficiency of standard
encoders, based on image to image (I2I) translation-based methods and cross-modality prediction; (ii) to investigate the coding efficiency of end-to-end learningbased multi-modal image codecs using state-of-the-art learning-based encoders to devise novel techniques capable of surpass standard encoders. Overall, the project seeks to explore multi-dimensional and multimodal characteristics to achieve better compression rates than current standards. |
|||||
| Reference: | 2022.09914.PTDC | |||||
| Funding: | FCT | |||||
| Approval Date: | 09-12-2022 | |||||
|
||||||
| Team: | Lucas Arrabal Thomaz, Pedro Antonio Amado Assunção, Luís Miguel de Oliveira Pegado de Noronha e Távora, Sérgio Manuel Maciel de Faria, Daniel Filipe da Silva Nicolau, Nicolas David Freire Vasconcellos, João Oliveira Parracho, Eduardo António Barros da Silva | |||||
| Groups: | Multimedia Signal Processing – Lr | |||||
| Partners: | Universidade Federal do Rio de Janeiro | |||||
| Local Coordinator: | Lucas Arrabal Thomaz | |||||
|
|
This project falls under the following United Nations Strategic Development Goals (SDGs):
