Zobrazeno 1 - 10
of 184
pro vyhledávání: '"Gongping, Yang"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 160-175 (2025)
Remote sensing change detection (CD) is a crucial task for observing and analyzing dynamic land cover alterations. Many CD methods based on deep learning demonstrate strong performance, but their effectiveness is influenced by the choice of encoder a
Externí odkaz:
https://doaj.org/article/289004e7f1e449b48252ea29bc73debc
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11761-11776 (2024)
Change detection (CD) aims to identify surface changes from bitemporal remote sensing (RS) images, which is a crucial and challenging topic in RS. In recent years, RS images CD has achieved significant advancements through the use of convolutional ne
Externí odkaz:
https://doaj.org/article/1fb072ec85404960920c0a9eccea1a42
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 8477-8489 (2024)
With the advancement of satellite technology, the application space of change detection (CD) in remote sensing images is continuously expanding. However, the development of satellite remote sensing technology is still ongoing, and limited resolution
Externí odkaz:
https://doaj.org/article/82b85a4ac44a407ea57120a0492a3cba
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 5607-5622 (2022)
Semantic segmentation of high spatial resolution (HSR) remote sensing images (RSIs) plays an important role in many applications. However, HSR RSIs have significantly larger spatial sizes than typical natural images, which results in fewer valuable s
Externí odkaz:
https://doaj.org/article/9d508a13af2e48b987a38e6cbde0edc8
Encoding Coefficient Similarity-Based Multifeature Sparse Representation for Finger Vein Recognition
Publikováno v:
IET Biometrics, Vol 2023 (2023)
Finger vein recognition is a promising biometric technology that has received significant research attention. However, most of the existing works often relied on a single feature, which failed to fully exploit the discriminative information in finger
Externí odkaz:
https://doaj.org/article/46b4fe75313d42b89707a29a4aa4d4b4
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 44:8585-8595
Fruit detection is essential for harvesting robot platforms. However, complicated environmental attributes such as illumination variation and occlusion have made fruit detection a challenging task. In this study, a Transformer-based mask region-based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7873cefc3fb86e8475744edb8bc9a793
https://doi.org/10.3233/jifs-222954
https://doi.org/10.3233/jifs-222954
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 44:7195-7210
Embedding similarity-based methods obtained good results in unsupervised anomaly detection (AD). This kind of method usually used feature vectors from a model pre-trained by ImageNet to calculate scores by measuring the similarity between test sample
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41449e6fa0ac0e7b338f355b5614d00f
https://doi.org/10.3233/jifs-222595
https://doi.org/10.3233/jifs-222595
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 33:1979-1993
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::622e8858b09d75570023c1eaf46c3d07
https://doi.org/10.1109/tcsvt.2022.3218284
https://doi.org/10.1109/tcsvt.2022.3218284
Publikováno v:
IEEE Access, Vol 7, Pp 28185-28195 (2019)
In finger vein recognition, vein points-based methods classified the image points into vein points and non-vein points and only measured the vein points for the recognition. All points-based methods utilized the features of all points regardless of t
Externí odkaz:
https://doaj.org/article/8836c6a7dc744990bdf24cbf9bb4dd15
Publikováno v:
International Journal of Machine Learning and Cybernetics. 14:2563-2574
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71acf3693488702ee9689537fd8ea2c9
https://doi.org/10.1007/s13042-023-01782-0
https://doi.org/10.1007/s13042-023-01782-0