Zobrazeno 1 - 10
of 2 091
pro vyhledávání: '"Ferrés, A"'
Autor:
Casaburi, Pasquale, Dall'Amico, Lorenzo, Gozzi, Nicolò, Kalimeri, Kyriaki, Sapienza, Anna, Schifanella, Rossano, Di Matteo, T., Ferres, Leo, Mazzoli, Mattia
The COVID19 pandemic highlighted the importance of non-traditional data sources, such as mobile phone data, to inform effective public health interventions and monitor adherence to such measures. Previous studies showed how socioeconomic characterist
Externí odkaz:
http://arxiv.org/abs/2405.19141
Autor:
Hernandez, Andres, Miao, Zhongqi, Vargas, Luisa, Dodhia, Rahul, Arbelaez, Pablo, Ferres, Juan M. Lavista
The alarming decline in global biodiversity, driven by various factors, underscores the urgent need for large-scale wildlife monitoring. In response, scientists have turned to automated deep learning methods for data processing in wildlife monitoring
Externí odkaz:
http://arxiv.org/abs/2405.12930
Autor:
Tadesse, Girmaw Abebe, Robinson, Caleb, Hacheme, Gilles Quentin, Zaytar, Akram, Dodhia, Rahul, Shawa, Tsering Wangyal, Ferres, Juan M. Lavista, Kreike, Emmanuel H.
This study explores object detection in historical aerial photographs of Namibia to identify long-term environmental changes. Specifically, we aim to identify key objects -- Waterholes, Omuti homesteads, and Big trees -- around Oshikango in Namibia u
Externí odkaz:
http://arxiv.org/abs/2404.08544
Autor:
Ahamed, Shadab, Xu, Yixi, Bloise, Ingrid, O, Joo H., Uribe, Carlos F., Dodhia, Rahul, Ferres, Juan L., Rahmim, Arman
Publikováno v:
Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124641Q (3 April 2023)
Automated slice classification is clinically relevant since it can be incorporated into medical image segmentation workflows as a preprocessing step that would flag slices with a higher probability of containing tumors, thereby directing physicians a
Externí odkaz:
http://arxiv.org/abs/2403.07105
Autor:
Zaytar, Akram, Robinson, Caleb, Hacheme, Gilles Q., Tadesse, Girmaw A., Dodhia, Rahul, Ferres, Juan M. Lavista, Hughey, Lacey F., Stabach, Jared A., Amoke, Irene
Rare object detection is a fundamental task in applied geospatial machine learning, however is often challenging due to large amounts of high-resolution satellite or aerial imagery and few or no labeled positive samples to start with. This paper addr
Externí odkaz:
http://arxiv.org/abs/2403.02736
Autor:
Robinson, Caleb, Corley, Isaac, Ortiz, Anthony, Dodhia, Rahul, Ferres, Juan M. Lavista, Najafirad, Peyman
Fully understanding a complex high-resolution satellite or aerial imagery scene often requires spatial reasoning over a broad relevant context. The human object recognition system is able to understand object in a scene over a long-range relevant con
Externí odkaz:
http://arxiv.org/abs/2401.06762
Autor:
Roman, Anthony Cintron, Vaughan, Jennifer Wortman, See, Valerie, Ballard, Steph, Torres, Jehu, Robinson, Caleb, Ferres, Juan M. Lavista
This paper introduces a no-code, machine-readable documentation framework for open datasets, with a focus on responsible AI (RAI) considerations. The framework aims to improve comprehensibility, and usability of open datasets, facilitating easier dis
Externí odkaz:
http://arxiv.org/abs/2312.06153
Autor:
Fabian, Zalan, Miao, Zhongqi, Li, Chunyuan, Zhang, Yuanhan, Liu, Ziwei, Hernández, Andrés, Montes-Rojas, Andrés, Escucha, Rafael, Siabatto, Laura, Link, Andrés, Arbeláez, Pablo, Dodhia, Rahul, Ferres, Juan Lavista
Due to deteriorating environmental conditions and increasing human activity, conservation efforts directed towards wildlife is crucial. Motion-activated camera traps constitute an efficient tool for tracking and monitoring wildlife populations across
Externí odkaz:
http://arxiv.org/abs/2311.01064
Autor:
Pereira, Mayana, Kshirsagar, Meghana, Mukherjee, Sumit, Dodhia, Rahul, Ferres, Juan Lavista, de Sousa, Rafael
Differentially private (DP) synthetic data sets are a solution for sharing data while preserving the privacy of individual data providers. Understanding the effects of utilizing DP synthetic data in end-to-end machine learning pipelines impacts areas
Externí odkaz:
http://arxiv.org/abs/2310.19250
Autor:
Schoedel, Rainer, Longmore, Steve, Henshaw, Jonny, Ginsburg, Adam, Bally, John, Feldmeier, Anja, Hosek, Matt, Lara, Francisco Nogueras, Ciurlo, Anna, Chevance, Mélanie, Kruijssen, J. M. Diederik, Klessen, Ralf, Ponti, Gabriele, Amaro-Seoane, Pau, Anastasopoulou, Konstantina, Anderson, Jay, Arias, Maria, Barnes, Ashley T., Battersby, Cara, Bono, Giuseppe, Ferres, Lucía Bravo, Bryant, Aaron, Gonzáalez, Miguel Cano, Cassisi, Santi, Chaves-Velasquez, Leonardo, Conte, Francesco, Ramos, Rodrigo Contreras, Cotera, Angela, Crowe, Samuel, di Teodoro, Enrico, Do, Tuan, Eisenhauer, Frank, Enokiya, Rei, Fedriani, Rubén, Friske, Jennifer K. S., Gadotti, Dimitri, Gallart, Carme, Calvente, Teresa Gallego, Cano, Eulalia Gallego, Fuentes, Pablo García, Marín, Macarena García, Gardini, Angela, Gautam, Abhimat K., Ghez, Andrea, Gillessen, Stefan, Gouda, Naoteru, Gualandris, Alessia, Guarcello, Mario Giuseppe, Gutermuth, Robert, Haggard, Daryl, Hankins, Matthew, Hu, Yue, Kano, Ryohei, Kauffmann, Jens, Lau, Ryan, Lazarian, Alexandre, Libralato, Mattia, Lu, Anan, Lu, Xing, Lu, Jessica R., Luetzgendorf, Nora, Magorrian, John, Mandel, Shifra, Markoff, Sera, Arranz, Álvaro Martínez, Mastrobuono-Battisti, Alessandra, Melamed, Maria, Mills, Elisabeth, Mori, Kaya, Morris, Mark, Murchikova, Elena, Nagata, Tetsuya, Najarro, Francisco, Nandakumar, Govind, Nataf, David, Neumayer, Nadine, Nishiyama, Shogo, Nobukawa, Masayoshi, Paré, Dylan M, Peissker, Florian, Petkova, Maya, Pillai, Thushara G. S., Román, Mike Rich Carlos, Rugel, Michael, Ryde, Nils, Sabha, Nadeen, Bermúdez, Joel Sánchez, Sánchez-Monge, Álvaro, Schultheis, Mathias, Shao, Lijing, Shinnaga, Hiroko, Simpson, Janet, Takekawa, Shunya, Tan, Jonathan C., Thorsbro, Brian, Torne, Pablo, Tress, Robin Goppala, Uchiyam, Hideki, Valenti, Elena, van der Marel, Roeland, Verberne, Sill, Vermot, Pierre, von Fellenberg, Sebastiano, Walker, Daniel, Witzel, Gunther, Xu, Siyao, Yano, Taihei, Yusef-Zadeh, Farhad, Zajaček, Michal, Zoccali, Manuela
The inner hundred parsecs of the Milky Way hosts the nearest supermassive black hole, largest reservoir of dense gas, greatest stellar density, hundreds of massive main and post main sequence stars, and the highest volume density of supernovae in the
Externí odkaz:
http://arxiv.org/abs/2310.11912