Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Sherrie Wang"'
Publikováno v:
Cancer Nanotechnology, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Background The addition of the cyclin dependent kinase inhibitor (CDKi) dinaciclib to Poly-(ADP-ribose) polymerase inhibitor (PARPi) therapy is a strategy to overcome resistance to PARPi in tumors that exhibit homologous recombination (HR) d
Externí odkaz:
https://doaj.org/article/bcb38076fd6e4bebba02ff716de87352
Autor:
Philippe Rufin, Sherrie Wang, Sá Nogueira Lisboa, Jan Hemmerling, Mirela G. Tulbure, Patrick Meyfroidt
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104149- (2024)
Satellite-based field delineation has entered a quasi-operational stage due to recent advances in machine learning for computer vision. Transfer learning allows for the resource-efficient transfer of pre-trained field delineation models across hetero
Externí odkaz:
https://doaj.org/article/f4501e0c6bb44445bff01730b6e49de0
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-14 (2024)
Abstract Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning method
Externí odkaz:
https://doaj.org/article/5bd59714a1e0442fa90e073dcd11187f
Autor:
A Patrick Behrer, Sherrie Wang
Publikováno v:
Environmental Research Letters, Vol 19, Iss 8, p 084010 (2024)
Wildfires throughout western North America produce smoke plumes that can stretch across the agricultural regions of the American Midwest. Climate change may increase the number and size of these fires and subsequent smoke plumes. These smoke plumes c
Externí odkaz:
https://doaj.org/article/584699f4a12c49b7a2fe9e9801996315
Publikováno v:
Remote Sensing, Vol 15, Iss 17, p 4123 (2023)
Crop type maps are critical for tracking agricultural land use and estimating crop production. Remote sensing has proven an efficient and reliable tool for creating these maps in regions with abundant ground labels for model training, yet these label
Externí odkaz:
https://doaj.org/article/7b48f8bf15854da9a3020a49c331f108
Publikováno v:
Otolaryngology Case Reports, Vol 23, Iss , Pp 100433- (2022)
Externí odkaz:
https://doaj.org/article/09142a498ecf4d2a8162debd3354661b
Publikováno v:
Remote Sensing, Vol 14, Iss 22, p 5738 (2022)
Crop field boundaries aid in mapping crop types, predicting yields, and delivering field-scale analytics to farmers. Recent years have seen the successful application of deep learning to delineating field boundaries in industrial agricultural systems
Externí odkaz:
https://doaj.org/article/35517a6cb4a84ef0a07714ff6d963bfa
Autor:
Ju Young Lee, Sherrie Wang, Anjuli Jain Figueroa, Rob Strey, David B. Lobell, Rosamond L. Naylor, Steven M. Gorelick
Publikováno v:
Remote Sensing, Vol 14, Iss 3, p 703 (2022)
In India, the second-largest sugarcane producing country in the world, accurate mapping of sugarcane land is a key to designing targeted agricultural policies. Such a map is not available, however, as it is challenging to reliably identify sugarcane
Externí odkaz:
https://doaj.org/article/6afc1450994b43f392a1792575d49975
Publikováno v:
Environmental Research Letters, Vol 16, Iss 12, p 125002 (2021)
High resolution crop type maps are an important tool for improving food security, and remote sensing is increasingly used to create such maps in regions that possess ground truth labels for model training. However, these labels are absent in many reg
Externí odkaz:
https://doaj.org/article/e7a19303e92f44438d22608e03ce1239
Autor:
Sherrie Wang, Stefania Di Tommaso, Joey Faulkner, Thomas Friedel, Alexander Kennepohl, Rob Strey, David B. Lobell
Publikováno v:
Remote Sensing, Vol 12, Iss 18, p 2957 (2020)
High resolution satellite imagery and modern machine learning methods hold the potential to fill existing data gaps in where crops are grown around the world at a sub-field level. However, high resolution crop type maps have remained challenging to c
Externí odkaz:
https://doaj.org/article/eb65dcf10928497689fe2824b4edc1d7