Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Hsiuhan Lexie Yang"'
Autor:
Hsiuhan Lexie Yang, Melanie Laverdiere, Taylor Hauser, Benjamin Swan, Erik Schmidt, Jessica Moehl, Andrew Reith, Daniel Adams, Bennett Morris, Jacob McKee, Matthew Whitehead, Mark Tuttle
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract Leveraging high performance computing, remote sensing, geographic data science, machine learning, and computer vision, Oak Ridge National Laboratory has partnered with Federal Emergency Management Agency (FEMA) to build a baseline structure
Externí odkaz:
https://doaj.org/article/3c1f7eaa515e4ffdb7e604ae7320d78a
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 9122-9138 (2024)
The use of convolutional neural networks (CNNs) for building extraction from remote sensing images has been widely studied and many public datasets have been made available for accelerating development of these CNN models. Yet adapting pretrained mod
Externí odkaz:
https://doaj.org/article/7b455a5fcfbd4d12b4bfc4041ef0462c
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16:1113-1129
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffae9a45417b098ee1a598935b44a932
https://doi.org/10.1109/jstars.2022.3230625
https://doi.org/10.1109/jstars.2022.3230625
Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f330efbf289d697e99ee1610ac485762
https://doi.org/10.1002/essoar.10508586.1
https://doi.org/10.1002/essoar.10508586.1
Autor:
Hsiuhan Lexie Yang, Nikhil Makkar
Publikováno v:
IGARSS
Supervised semantic segmentation methods provide state-of-the-art performance, but their performance is limited by the amount of quality labeled data they need for training. Scarcity of labeled data and non-transferablity of models, due to cross-doma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee5d06322b51e2a4626459b74975d15c
https://doi.org/10.1109/igarss39084.2020.9323863
https://doi.org/10.1109/igarss39084.2020.9323863
Autor:
Hsiuhan Lexie Yang, Jeanette Weaver, Andrew Reith, Dalton Lunga, Budhendra L. Bhaduri, Jiangye Yuan
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11:962-977
Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1a1e63579270e18d3815dee6ea3ed6f
https://doi.org/10.1109/jstars.2018.2795753
https://doi.org/10.1109/jstars.2018.2795753
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 10:262-276
Low-cost unmanned airborne vehicles (UAVs) are emerging as a promising platform for remote-sensing data acquisition to satisfy the needs of wide range of applications. Utilizing UAVs, which are equipped with directly georeferenced RGB-frame cameras a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::babd5edeb311eec416397d74253a941f
https://doi.org/10.1109/jstars.2016.2520929
https://doi.org/10.1109/jstars.2016.2520929
Publikováno v:
IGARSS
Most current state-of-the-art methods for semantic segmentation on remote sensing imagery require large labeled data, which is scarcely available. Due to the distribution shifting phenomenon inherent in remote sensing imagery, the reuse of pre-traine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6ef7d9370f1dd1b7ee27d8efa5df5dc
https://doi.org/10.1109/igarss.2019.8900277
https://doi.org/10.1109/igarss.2019.8900277
Autor:
Anne Berres, Amy Rose, Kuldeep Kurte, Hsiuhan Lexie Yang, Mark Coletti, Benjamin Liebersohn, Daniel Graves, Dalton Lunga, Jibonananda Sanyal
Publikováno v:
Concurrency and Computation: Practice and Experience. 31
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5311eea317665a5135ffece9970a1a1
https://doi.org/10.1002/cpe.5305
https://doi.org/10.1002/cpe.5305
Autor:
Hsiuhan Lexie Yang, Melba M. Crawford
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 9:543-555
Adapting a pretrained classifier with unlabeled samples from an image for classification of another related image is a common domain adaptation strategy. However, traditional adaptation methods are not effective when the drift of spectral signatures
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96b5a6c4332db2ca155a99d57448012d
https://doi.org/10.1109/jstars.2015.2449738
https://doi.org/10.1109/jstars.2015.2449738