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pro vyhledávání: '"Hernandez, Jefferson"'
We propose to use automatically generated instruction-following data to improve the zero-shot capabilities of a large multimodal model with additional support for generative and image editing tasks. We achieve this by curating a new multimodal instru
Externí odkaz:
http://arxiv.org/abs/2406.11262
We propose ViC-MAE, a model that combines both Masked AutoEncoders (MAE) and contrastive learning. ViC-MAE is trained using a global featured obtained by pooling the local representations learned under an MAE reconstruction loss and leveraging this r
Externí odkaz:
http://arxiv.org/abs/2303.12001
Multiple-Object Tracking (MOT) is of crucial importance for applications such as retail video analytics and video surveillance. Object detectors are often the computational bottleneck of modern MOT systems, limiting their use for real-time applicatio
Externí odkaz:
http://arxiv.org/abs/1908.04349
Autor:
Hernandez, Jefferson, Abad, Andres G.
A restricted Boltzmann machine (RBM) is a generative neural-network model with many novel applications such as collaborative filtering and acoustic modeling. An RBM lacks the capacity to retain memory, making it inappropriate for dynamic data modelin
Externí odkaz:
http://arxiv.org/abs/1804.10839
Masked Autoencoders (MAEs) learn self-supervised representations by randomly masking input image patches and a reconstruction loss. Alternatively, contrastive learning self-supervised methods encourage two versions of the same input to have a similar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38b70f9052a769d862c569191dcfef68
http://arxiv.org/abs/2303.12001
http://arxiv.org/abs/2303.12001
Publikováno v:
Repositório Institucional da UFSC
Universidade Federal de Santa Catarina (UFSC)
instacron:UFSC
Universidade Federal de Santa Catarina (UFSC)
instacron:UFSC
Dissertação (mestrado profissional) - Universidade Federal de Santa Catarina, Centro de Ciências Biológicas, Programa de Pós-Graduação em Perícias Criminais Ambientais, Florianópolis, 2021. No licenciamento ambiental de atividades de lavra a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::bffd12a37ed3e13db7247b9e1373f097
https://repositorio.ufsc.br/handle/123456789/229783
https://repositorio.ufsc.br/handle/123456789/229783
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