Zobrazeno 1 - 10
of 552
pro vyhledávání: '"Zhu Anna"'
Scene graph generation (SGG) aims to automatically map an image into a semantic structural graph for better scene understanding. It has attracted significant attention for its ability to provide object and relation information, enabling graph reasoni
Externí odkaz:
http://arxiv.org/abs/2310.00712
Automatic few-shot font generation (AFFG), aiming at generating new fonts with only a few glyph references, reduces the labor cost of manually designing fonts. However, the traditional AFFG paradigm of style-content disentanglement cannot capture the
Externí odkaz:
http://arxiv.org/abs/2309.00827
Publikováno v:
Pattern Recognition 2023
The scene text removal (STR) task aims to remove text regions and recover the background smoothly in images for private information protection. Most existing STR methods adopt encoder-decoder-based CNNs, with direct copies of the features in the skip
Externí odkaz:
http://arxiv.org/abs/2306.09593
Autor:
Lyu, Guangtao, Zhu, Anna
Publikováno v:
2022 IEEE International Conference on Multimedia and Expo (ICME)
Scene text removal (STR) is a challenging task due to the complex text fonts, colors, sizes, and background textures in scene images. However, most previous methods learn both text location and background inpainting implicitly within a single network
Externí odkaz:
http://arxiv.org/abs/2306.07842
Pursuing educational qualifications later in life is an increasingly common phenomenon within OECD countries since technological change and automation continues to drive the evolution of skills needed in many professions. We focus on the causal impac
Externí odkaz:
http://arxiv.org/abs/2304.01490
Publikováno v:
In Sensors and Actuators: B. Chemical 15 May 2024 407
Publikováno v:
In Journal of Hazardous Materials 5 May 2024 469
Publikováno v:
In Sensors and Actuators: B. Chemical 15 April 2024 405
Autor:
Roden, M., Al-Hasani, H., Belgardt, B., Lammert, E., Bönhof, G., Geerling, G., Herder, C., Icks, A., Jandeleit-Dahm, K., Kotzka, J., Kuß, O., Rathmann, W., Schlesinger, S., Schrauwen-Hinderling, V., Szendroedi, J., Trenkamp, S., Wagner, R., Weber, Katharina S., Schlesinger, Sabrina, Lang, Alexander, Straßburger, Klaus, Maalmi, Haifa, Zhu, Anna, Zaharia, Oana-Patricia, Strom, Alexander, Bönhof, Gidon J., Goletzke, Janina, Trenkamp, Sandra, Wagner, Robert, Buyken, Anette E., Lieb, Wolfgang, Roden, Michael, Herder, Christian
Publikováno v:
In Nutrition, Metabolism and Cardiovascular Diseases April 2024 34(4):911-924
Autor:
Sansone, Dario, Zhu, Anna
Using high-quality nation-wide social security data combined with machine learning tools, we develop predictive models of income support receipt intensities for any payment enrolee in the Australian social security system between 2014 and 2018. We sh
Externí odkaz:
http://arxiv.org/abs/2011.12057