pinto 1 pinus 1 pipe 15 pistachio 2 pistachio nuts 1 pizza 18 pizzas 3 place 3 plane 9 planks 2 plant 28 plant management 4 planting 1 plants 485 plants wallpaper 7 plasma 1 plastic 40 plate 4 platform 3 play 27 Play airline 4 played 1 player 2 pl...
pinto 1 pinus 1 pipe 15 pistachio 2 pistachio nuts 1 pizza 18 pizzas 3 place 3 plane 9 planks 2 plant 28 plant management 4 planting 1 plants 485 plants wallpaper 7 plasma 1 plastic 40 plate 4 platform 3 play 27 Play airline 4 played 1 player 2 pl...
ravipinto / docker-images ravredd / docker-images rcarmonad / docker-images rcnazar / docker-images rdwinter2 / docker-images realmfoo / docker-images refactoror / docker-images refnode / oracle-docker-images ReneNyffenegger / oracle-docker-images reybis / docker-images rfrp ...
José Dorado 2, José María Bengochea-Guevara 1, Jesús Conesa-Muñoz 1, César Fernández-Quintanilla 2 and Ángela Ribeiro 1 1 Centre for Automation and Robotics, Spanish National Research Council, CSIC-UPM, Argandadel Rey, 28500 Madrid, Spain; jose.bengochea@car.upm-csic.es (J.M.B,...
Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders1. However, the development of AI models requires substantial anno
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Confocal laser scanning microscopy (CLSM) images of R36A and R36A-CSP2 biofilms.Margarida CarroloFrancisco Rodrigues PintoJosé MeloCristinoMário Ramirez
Tranheden, W.; Olsson, V.; Pinto, J.; Svensson, L. DACS: Domain Adaptation via Cross-domain Mixed Sampling. In Proceedings of the 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, USA, 5–9 January 2021; pp. 1378–1388. [Google Scholar] [CrossRef]...
The I-JEPA predictor correctly captures posi- tional uncertainty and produces high-level object parts with the correct pose (e.g., back of the bird and top of the car). 9. Ablations Predicting in representation space. Table 7 compares low-shot ...