Zobrazeno 1 - 10
of 1 042
pro vyhledávání: '"Boehlen, A"'
Autor:
Böhlen, Marc, Sughiarta, Gede, Kurnianingsih, Atiek, Gopaladinne, Srikar Reddy, Shrivastava, Sujay, Gorla, Hemanth Kumar Reddy
This paper describes spatially aware Artificial Intelligence, GeoAI, tailored for small organizations such as NGOs in resource constrained contexts where access to large datasets, expensive compute infrastructure and AI expertise may be restricted. W
Externí odkaz:
http://arxiv.org/abs/2408.17361
Autor:
Böhlen, Marc, Chen, Ruolin, Dong, Xiaoxu, Gopaladinne, Srikar, Gorla, Hemanth, Kandukuri, Divya, Mansfield, Sean
This text describes experiences gained across a two-year test period during which two generations of Generative Artificial Intelligence (A.I.) systems were incorporated into an interdisciplinary, university level course on A.I. for art and design pra
Externí odkaz:
http://arxiv.org/abs/2401.16268
Frequent queries on semi-structured hierarchical data are Content-and-Structure (CAS) queries that filter data items based on their location in the hierarchical structure and their value for some attribute. We propose the Robust and Scalable Content-
Externí odkaz:
http://arxiv.org/abs/2209.05126
Answering connectivity queries is fundamental to fully dynamic graphs where edges and vertices are inserted and deleted frequently. Existing work proposes data structures and algorithms with worst-case guarantees. We propose a new data structure, the
Externí odkaz:
http://arxiv.org/abs/2207.06887
Autor:
Böhlen, Till Tobias, Zeverino, Michele, Germond, Jean‐François, Kinj, Rémy, Schiappacasse, Luis, Bochud, François, Herrera, Fernanda, Bourhis, Jean, Moeckli, Raphaël
Publikováno v:
In Radiotherapy and Oncology December 2024 201
Autor:
Böhlen, Till Tobias, Psoroulas, Serena, Aylward, Jack D, Beddar, Sam, Douralis, Alexandros, Delpon, Grégory, Garibaldi, Cristina, Gasparini, Alessia, Schüler, Emil, Stephan, Frank, Moeckli, Raphaël, Subiel, Anna
Publikováno v:
In Radiotherapy and Oncology November 2024 200
Autor:
Vens, C., van Luijk, P., Vogelius, R.I., El Naqa, I., Humbert-Vidan, L., von Neubeck, C., Gomez-Roman, N., Bahn, E., Brualla, L., Böhlen, T.T., Ecker, S., Koch, R., Handeland, A., Pereira, S., Possenti, L., Rancati, T., Todor, D., Vanderstraeten, B., Van Heerden, M., Ullrich, W., Jackson, M., Alber, M., Marignol, L.
Publikováno v:
In Radiotherapy and Oncology July 2024 196
Publikováno v:
ICMLA 2021
Image classifiers work effectively when applied on structured images, yet they often fail when applied on images with very high visual complexity. This paper describes experiments applying state-of-the-art object classifiers toward a unique set of im
Externí odkaz:
http://arxiv.org/abs/2109.12040
Autor:
Böhlen, Till Tobias, Germond, Jean‐François, Desorgher, Laurent, Veres, Izabella, Bratel, Andreas, Landström, Eric, Engwall, Erik, Herrera, Fernanda G., Ozsahin, Esat Mahmut, Bourhis, Jean, Bochud, François, Moeckli, Raphaël
Publikováno v:
In Radiotherapy and Oncology May 2024 194
Autor:
Böhlen, Marc
Publikováno v:
9th Conference on Computation, Communication, Aesthetics & X 2021
This text argues for the potential of machine learning infused classification systems as vectors for a technically-engaged and constructive technology critique. The text describes this potential with several experiments in image data creation and neu
Externí odkaz:
http://arxiv.org/abs/2104.03886