Here, we offer the first global river flood prediction framework based on the newly published Caravan dataset.
no code implementations • 10 Nov 2022 • Abdelhamid Ezzerg, Thomas Merritt, Kayoko Yanagisawa, Piotr Bilinski, Magdalena Proszewska, Kamil Pokora, Renard Korzeniowski, Roberto Barra-Chicote, Daniel Korzekwa
Regional accents of the same language affect not only how words are pronounced (i. e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intonation.
no code implementations • 17 Dec 2020 • Christian Schroeder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski
Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world.
Creating realistic human videos entails the challenge of being able to simultaneously generate both appearance, as well as motion.
2) We show that it is possible to detect informal settlements using freely available low-resolution (LR) data, in contrast to previous studies that use very-high resolution (VHR) satellite and aerial imagery, something that is cost-prohibitive for NGOs.
We propose a novel approach for rapid segmentation of flooded buildings by fusing multiresolution, multisensor, and multitemporal satellite imagery in a convolutional neural network.
We propose two effective methods for detecting and mapping the locations of informal settlements.
Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals.
We propose a novel end-to-end trainable, deep, encoder-decoder architecture for single-pass semantic segmentation.
Ranked #6 on Semantic Segmentation on CamVid