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Akademický článek

Deep-Learning-Based Automatic Sinkhole Recognition: Application to the Eastern Dead Sea

Autor: Osama Alrabayah, Danu Caus, Robert Alban Watson, Hanna Z. Schulten, Tobias Weigel, Lars Rüpke, Djamil Al-Halbouni

Publikováno v: Remote Sensing, Vol 16, Iss 13, p 2264 (2024)

Sinkholes can cause significant damage to infrastructures, agriculture, and endanger lives in active karst regions like the Dead Sea’s eastern shore at Ghor Al-Haditha. The common sinkhole mapping methods often require costly high-resolution data a

Externí odkaz: https://doaj.org/article/b92a994d40b74b02a380c7c06edbde2e

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Predicting fault stress level and stress drop using seismo-mechanical and statistical features derived from acoustic signals in laboratory stick-slip friction experiments and assesing feature importance via the derived models

Autor: Danu Caus, Harsh Grover, Thomas H. Goebel, Grzegorz Kwiatek, Tobias Weigel

Earthquake prediction relies on identification of distinctive patterns of precursory parameters that might precede a large earthquake. However, these patterns are typically not reliably observed in the field. Laboratory stick-slip experiments provide

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cce9b1870970ce19eaac46bb56439cb0
https://doi.org/10.5194/egusphere-egu23-1967

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Automatic geological structure recognition at the Dead Sea lakebed

Autor: Osama AlRabayah, Djamil Al-Halbouni, Robert A. Watson, Danu Caus, Harsh Grover, David Nakath, Lars Rüpke, Tobias Weigel

This research aims at developing and applying a machine learning based algorithm to detect geological structural features at the exposed Dead Sea shoreline. We focus on sinkhole, stream-channel and crack features that appear in different material at

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4577b30bf6fde05b53eaf031749ce103
https://doi.org/10.5194/icg2022-460

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Unlocking the potential of ML for Earth and Environment researchers

Autor: Tobias Weigel, Frauke Albrecht, Caroline Arnold, Danu Caus, Harsh Grover, Andrey Vlasenko

This presentation reports on support done under the aegis of Helmholtz AI for a wide range of machine learning based solutions for research questions related to Earth and Environmental sciences. We will give insight into typical problem statements fr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b519f37c98863e2aac404428d5db6b80
https://doi.org/10.5194/egusphere-egu22-7011

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See the Silence: Improving Visual-Only Voice Activity Detection by Optical Flow and RGB Fusion

Autor: Danu Caus, Simone Frintrop, Timo Gerkmann, Guillaume Carbajal

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030871550
ICVS

In this work, we propose a novel approach for visual voice activity detection (VAD), which is an important component of audio-visual tasks such as speech enhancement. We focus on optimizing the visual component and propose a two-stream approach based

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bf6cb1173f8ecd1347d3028fd342079a
https://doi.org/10.1007/978-3-030-87156-7_4

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