Global Land-Cover Mapping With Weak Supervision: Outcome of the 2020 IEEE GRSS Data Fusion Contest

Autor: Caleb Robinson, Kolya Malkin, Nebojsa Jojic, Huijun Chen, Rongjun Qin, Changlin Xiao, Michael Schmitt, Pedram Ghamisi, Ronny Hansch, Naoto Yokoya

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3185-3199 (2021)

This article presents the scientific outcomes of the 2020 Data Fusion Contest (DFC2020) organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. The 2020 Contest addressed the problem of a

Externí odkaz: https://doaj.org/article/528a0ede82f04100be73de48f671644d

2021 Data Fusion Contest: Geospatial Artificial Intelligence for Social Good [Technical Committees]

Autor: Naoto Yokoya, Colin Prieur, Pedram Ghamisi, Nebojsa Jojic, Ronny Hänsch, Hana Malha, Jocelyn Chanussot, Kolya Malkin, Caleb Robinson

Publikováno v: IEEE geoscience and remote sensing magazine
IEEE geoscience and remote sensing magazine, IEEE, 2021, 9 (1), pp.287-C3. ⟨10.1109/MGRS.2021.3055633⟩
IEEE Geoscience and Remote Sensing Magazine 9(2021)1, 287-C3

The 2021 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), promotes research on geospatial artificial intelligence (AI) for social good. The gl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e1419ba9c0dbfe3677c9a89652751ad
https://hal.archives-ouvertes.fr/hal-03430151

Mining Self-similarity: Label Super-Resolution with Epitomic Representations

Autor: Caleb Robinson, Nebojsa Jojic, Anthony Ortiz, Kolya Malkin

Publikováno v: Computer Vision – ECCV 2020 ISBN: 9783030585730
ECCV (26)

We show that simple patch-based models, such as epitomes (Jojic et al., 2003), can have superior performance to the current state of the art in semantic segmentation and label super-resolution, which uses deep convolutional neural networks. We derive

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::81a3a431f14ba49bd834516cc93f1304
https://doi.org/10.1007/978-3-030-58574-7_32

Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data

Autor: Kolya Malkin, Rachel Soobitsky, Caleb Robinson, Nebojsa Jojic, Le Hou, Jacob Czawlytko, Bistra Dilkina

Publikováno v: CVPR

In this paper we propose multi-resolution data fusion methods for deep learning-based high-resolution land cover mapping from aerial imagery. The land cover mapping problem, at country-level scales, is challenging for common deep learning methods due

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::15866f13d83b352fcc65b990ce0ceab9
https://doi.org/10.1109/cvpr.2019.01301