Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Minchao Ye"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 19640-19667 (2024)
Fine-grained image recognition (FGIR), unlike traditional coarse-grained recognition, is centered on distinguishing fine-level subclasses within broader semantic categories. It holds significant scientific research value, particularly in remote sensi
Externí odkaz:
https://doaj.org/article/1cbc3dc6119840a1a24822c6b2883140
Publikováno v:
IET Computer Vision, Vol 17, Iss 7, Pp 739-749 (2023)
Abstract Small‐sample‐size problem is always a challenge for hyperspectral image (HSI) classification. Considering the co‐occurrence of land‐cover classes between similar scenes, transfer learning can be performed, and cross‐scene classific
Externí odkaz:
https://doaj.org/article/725f35de49db4112affe0f684ed8ebae
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 2473-2483 (2021)
Hyperspectral images (HSIs) include hundreds of spectral bands, which lead to Hughes phenomenon in classification task and decrease the classification accuracy. Feature selection can remove redundant and noisy features in the HSIs to overcome this ph
Externí odkaz:
https://doaj.org/article/0b3dc7860f794a77a6acae15c0610932
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 5932-5949 (2021)
In the classification of hyperspectral images (HSIs), too many spectral bands (features) cause feature redundancy, resulting in a reduction in classification accuracy. In order to solve this problem, it is a good method to use feature selection to se
Externí odkaz:
https://doaj.org/article/1e81458f9075457fa51d98e4d44bd2db
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 3164-3178 (2020)
Lack of labeled training samples is a big challenge for hyperspectral image (HSI) classification. In recent years, cross-scene classification has become a new research topic. In cross-scene classification, two closely related HSI scenes are considere
Externí odkaz:
https://doaj.org/article/05af1dc45243429b8cd45a32587fee91
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S25, Pp 1-10 (2019)
Abstract Background Cost-sensitive algorithm is an effective strategy to solve imbalanced classification problem. However, the misclassification costs are usually determined empirically based on user expertise, which leads to unstable performance of
Externí odkaz:
https://doaj.org/article/2654d23d80cb48d8aa490d8b649a685d
Publikováno v:
PLoS ONE, Vol 10, Iss 8, p e0135090 (2015)
Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known a
Externí odkaz:
https://doaj.org/article/96688ff3f1404d06ae7d1e3ce3facf17
Publikováno v:
PLoS ONE, Vol 10, Iss 9, p e0138279 (2015)
Externí odkaz:
https://doaj.org/article/a18bd3faf4a440deae0a21c152004c47
Publikováno v:
Advances in Hyperspectral Image Processing Techniques. :363-403
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaf3d1b369ece7a4f06dc40112deb25f
https://doi.org/10.1002/9781119687788.ch13
https://doi.org/10.1002/9781119687788.ch13
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-13
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6aa4e32de6504cd3df20df7cfa1c614
https://doi.org/10.1109/tgrs.2022.3142941
https://doi.org/10.1109/tgrs.2022.3142941