Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Chenhong Sui"'
Publikováno v:
IEEE Access, Vol 11, Pp 84241-84257 (2023)
The technology of non-contact heart rate detection has been proven of great use. However, it is still limited by several challenges, particularly the influence of human motion and random disturbances, which significantly degrade the accuracy of the m
Externí odkaz:
https://doaj.org/article/5308b03b9dbe48a4a74c2583f1053fbd
Publikováno v:
IEEE Access, Vol 7, Pp 20676-20688 (2019)
Saliency-based methods have been widely used in the fusion of infrared (IR) and visible (VIS) images, which can highlight the salient object region and preserve the detailed background information simultaneously. However, most existing methods ignore
Externí odkaz:
https://doaj.org/article/a665bc58bd6649f48cfe6130068ab39e
Publikováno v:
Remote Sensing, Vol 11, Iss 20, p 2434 (2019)
In recent years, endmember variability has received much attention in the field of hyperspectral unmixing. To solve the problem caused by the inaccuracy of the endmember signature, the endmembers are usually modeled to assume followed by a statistica
Externí odkaz:
https://doaj.org/article/4488be1e804b45de95f75b34d46b4979
Publikováno v:
IEEE Sensors Journal. 22:4338-4346
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9ac559b9885838467e0f0f9cf2b7e9a
https://doi.org/10.1109/jsen.2022.3143852
https://doi.org/10.1109/jsen.2022.3143852
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ff4ef6d1fe719cf489c1baaba230252
https://doi.org/10.1109/lgrs.2021.3133549
https://doi.org/10.1109/lgrs.2021.3133549
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-15
Band selection is an effective means to alleviate the curse of dimensionality in hyperspectral data. Many methods select a compact and low redundant band subset, which is inadequate as it may degrade the classification performance. Instead, more emph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3be77c7823a0929e9a7f8654bb6078f
https://doi.org/10.1109/tgrs.2021.3068779
https://doi.org/10.1109/tgrs.2021.3068779
Publikováno v:
2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68d0d502e5db6621195ec9863ffb44d8
https://doi.org/10.1109/icarce55724.2022.10046623
https://doi.org/10.1109/icarce55724.2022.10046623
Publikováno v:
2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05d0722da5ac6dbf770a90384ffb8d0e
https://doi.org/10.1109/icarce55724.2022.10046567
https://doi.org/10.1109/icarce55724.2022.10046567
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:5054-5070
Convolutional neural networks (CNNs) have demo- nstrated outstanding performance on image classification. To classify the hyperspectral images (HSIs), existing CNN-based approaches commonly adopt the architecture using single or several fixed spatial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71bbfd5a4d55d19d4e1f85b81e2bde3e
https://doi.org/10.1109/tgrs.2020.3011943
https://doi.org/10.1109/tgrs.2020.3011943
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 70:1-12
Methods based on generative adversarial network (GAN) have been widely used in infrared and visible images fusion. However, these methods cannot perceive the discriminative parts of an image. Therefore, we introduce a multigrained attention module in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1052cced25632a70f6581d94029211e
https://doi.org/10.1109/tim.2020.3029360
https://doi.org/10.1109/tim.2020.3029360