Zobrazeno 1 - 10
of 238 907
pro vyhledávání: '"Remote sensing data"'
Autor:
Costarelli, Danilo, Piconi, Michele
In this paper, we provide two algorithms based on the theory of multidimensional neural network (NN) operators activated by hyperbolic tangent sigmoidal functions. Theoretical results are recalled to justify the performance of the here implemented al
Externí odkaz:
http://arxiv.org/abs/2412.00375
Autor:
Pang, Bo, Cheng, Sibo, Huang, Yuhan, Jin, Yufang, Guo, Yike, Prentice, I. Colin, Harrison, Sandy P., Arcucci, Rossella
Publikováno v:
Computers & Geosciences, Volume 195, 2025, 105783
Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent socioeconomic losses and environmental damage, but challenging because of the complexity of fire behaviour. Existing physics-based models are limited in pre
Externí odkaz:
http://arxiv.org/abs/2412.01400
Crop yield prediction is essential for agricultural planning but remains challenging due to the complex interactions between weather, climate, and management practices. To address these challenges, we introduce a deep learning-based multi-model calle
Externí odkaz:
http://arxiv.org/abs/2411.16989
Unleashing the power of remote sensing data in aquatic research: Guidelines for optimal utilization.
Autor:
Ogashawara, Igor1 (AUTHOR) igor.ogashawara@igb-berlin.de, Wollrab, Sabine1 (AUTHOR), Berger, Stella A.1 (AUTHOR), Kiel, Christine1 (AUTHOR), Jechow, Andreas2 (AUTHOR), Guislain, Alexis L. N.1 (AUTHOR), Gege, Peter3 (AUTHOR), Ruhtz, Thomas4 (AUTHOR), Hieronymi, Martin5 (AUTHOR), Schneider, Thomas6 (AUTHOR), Lischeid, Gunnar7 (AUTHOR), Singer, Gabriel A.8 (AUTHOR), Hölker, Franz1 (AUTHOR), Grossart, Hans‐Peter1 (AUTHOR), Nejstgaard, Jens C.1 (AUTHOR)
Publikováno v:
Limnology & Oceanography Letters. Dec2024, Vol. 9 Issue 6, p667-673. 7p.
Autor:
Liu, Ziqi1 (AUTHOR) lzq677@cumt.edu.cn, Xue, Yong2 (AUTHOR) wenping.yin@tum.de, Zhao, Jiaqi1 (AUTHOR) jiaqizhao@cumt.edu.cn, Yin, Wenping2,3 (AUTHOR) shengzhang@cumt.edu.cn, Zhang, Sheng2 (AUTHOR) tb22160010a41@cumt.edu.cn, Li, Pei2 (AUTHOR) mint_tao@cumt.edu.cn, He, Botao2 (AUTHOR)
Publikováno v:
Biomimetics (2313-7673). Nov2024, Vol. 9 Issue 11, p678. 23p.
Autor:
Peng, Dailiang1,2 (AUTHOR) pengdl@aircas.ac.cn, Cheng, Enhui1,2,3 (AUTHOR) chengenhui22@mails.ucas.ac.cn, Feng, Xuxiang4 (AUTHOR) fengxx@aircas.ac.cn, Hu, Jinkang1,2,3 (AUTHOR) hujinkang21@mails.ucas.ac.cn, Lou, Zihang5 (AUTHOR) lou.zihang@zju.edu.cn, Zhang, Hongchi1,2,3 (AUTHOR) zhanghongchi23@mails.ucas.ac.cn, Zhao, Bin6 (AUTHOR) binzhao@sdau.edu.cn, Lv, Yulong1,3 (AUTHOR) lvyulong24@mails.ucas.ac.cn, Peng, Hao3,7 (AUTHOR), Zhang, Bing1,3 (AUTHOR) zhangbing@aircas.ac.cn
Publikováno v:
Remote Sensing. Oct2024, Vol. 16 Issue 19, p3613. 16p.
Autor:
Guo, Long1,2 (AUTHOR) guolong21@mails.ucas.ac.cn, He, Zhongtai1,2 (AUTHOR) hzt@ies.ac.cn, Ren, Zhikun1,2 (AUTHOR) lixingao22@mails.ucas.ac.cn, Li, Xingao1,2,3 (AUTHOR) linlinli@ninhm.ac.cn, Li, Linlin3 (AUTHOR)
Publikováno v:
Remote Sensing. Nov2024, Vol. 16 Issue 21, p3925. 27p.
Multi-source remote sensing data classification has emerged as a prominent research topic with the advancement of various sensors. Existing multi-source data classification methods are susceptible to irrelevant information interference during multi-s
Externí odkaz:
http://arxiv.org/abs/2406.01245