Zobrazeno 1 - 10
of 5 849
pro vyhledávání: '"SCHMITT, MICHAEL"'
SenPa-MAE: Sensor Parameter Aware Masked Autoencoder for Multi-Satellite Self-Supervised Pretraining
Autor:
Prexl, Jonathan, Schmitt, Michael
This paper introduces SenPa-MAE, a transformer architecture that encodes the sensor parameters of an observed multispectral signal into the image embeddings. SenPa-MAE can be pre-trained on imagery of different satellites with non-matching spectral o
Externí odkaz:
http://arxiv.org/abs/2408.11000
Autor:
Ekim, Burak, Schmitt, Michael
In recent decades, the causes and consequences of climate change have accelerated, affecting our planet on an unprecedented scale. This change is closely tied to the ways in which humans alter their surroundings. As our actions continue to impact nat
Externí odkaz:
http://arxiv.org/abs/2406.19302
Autor:
Alexander, Duncan T. L., Meley, Hugo, Schmitt, Michael Marcus, Mundet, Bernat, Ghosez, Philippe, Triscone, Jean-Marc, Gariglio, Stefano
The atomic configuration of phases and their interfaces is fundamental to materials design and engineering. Here, we unveil a transition metal oxide interface, whose formation is driven by energetic influences - epitaxial tensile strain versus oxygen
Externí odkaz:
http://arxiv.org/abs/2401.08798
Autor:
Schmitt, Michael, Ahmadi, Seyed Ali, Xu, Yonghao, Taskin, Gulsen, Verma, Ujjwal, Sica, Francescopaolo, Hansch, Ronny
Publikováno v:
Published in IEEE Geoscience and Remote Sensing Magazine, vol. 11, no. 3, pp. 63-97, Sept. 2023
Carefully curated and annotated datasets are the foundation of machine learning, with particularly data-hungry deep neural networks forming the core of what is often called Artificial Intelligence (AI). Due to the massive success of deep learning app
Externí odkaz:
http://arxiv.org/abs/2310.19231
Synthetic aperture radar (SAR) images are widely used in remote sensing. Interpreting SAR images can be challenging due to their intrinsic speckle noise and grayscale nature. To address this issue, SAR colorization has emerged as a research direction
Externí odkaz:
http://arxiv.org/abs/2310.08705