Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Zhenpeng Feng"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16902-16916 (2024)
In recent decades, weakly supervised object localization (WSOL) has gained increasing attention in remote sensing. However, unlike optical images, remote sensing images (RSIs) often contain more complex scenes, which poses challenges for WSOL. Tradit
Externí odkaz:
https://doaj.org/article/5609d41e205e43b4bfed70ff94c68372
Publikováno v:
Remote Sensing, Vol 15, Iss 12, p 3103 (2023)
The integration of deep learning methods, especially Convolutional Neural Networks (CNN), and Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has been widely deployed in the field of radar signal processing. Nevertheless, these method
Externí odkaz:
https://doaj.org/article/83ddda816c3f437797fc8a52bb763fdb
Autor:
Zhenpeng Feng, Miloš Daković, Hongbing Ji, Xianda Zhou, Mingzhe Zhu, Xiyang Cui, Ljubiša Stanković
Publikováno v:
Remote Sensing, Vol 15, Iss 5, p 1254 (2023)
Generative adversarial networks (GANs) can synthesize abundant photo-realistic synthetic aperture radar (SAR) images. Some modified GANs (e.g., InfoGAN) are even able to edit specific properties of the synthesized images by introducing latent codes.
Externí odkaz:
https://doaj.org/article/7dadd6ba920f4348b7a097ad48273a54
Publikováno v:
Remote Sensing, Vol 14, Iss 1, p 204 (2022)
Deep learning has obtained remarkable achievements in computer vision, especially image and video processing. However, in synthetic aperture radar (SAR) image recognition, the application of DNNs is usually restricted due to data insufficiency. To au
Externí odkaz:
https://doaj.org/article/81ae50b4fc334e0eb92359cdb1e2f68a
Publikováno v:
Remote Sensing, Vol 13, Iss 20, p 4139 (2021)
Convolutional neural networks (CNNs) have successfully achieved high accuracy in synthetic aperture radar (SAR) target recognition; however, the intransparency of CNNs is still a limiting or even disqualifying factor. Therefore, visually interpreting
Externí odkaz:
https://doaj.org/article/654e18c3eebd4b72bcd95b0ce014db50
Publikováno v:
Sensors, Vol 21, Iss 13, p 4536 (2021)
Target recognition is one of the most challenging tasks in synthetic aperture radar (SAR) image processing since it is highly affected by a series of pre-processing techniques which usually require sophisticated manipulation for different data and co
Externí odkaz:
https://doaj.org/article/6e9990eedb85414dbeb2671affc23900
Publikováno v:
Remote Sensing, Vol 13, Iss 9, p 1772 (2021)
Synthetic aperture radar (SAR) image interpretation has long been an important but challenging task in SAR imaging processing. Generally, SAR image interpretation comprises complex procedures including filtering, feature extraction, image segmentatio
Externí odkaz:
https://doaj.org/article/4c581eba0f934a4da7dbd5e6ad3c78b5
Publikováno v:
Remote Sensing; Volume 15; Issue 12; Pages: 3103
The integration of deep learning methods, especially Convolutional Neural Networks (CNN), and Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has been widely deployed in the field of radar signal processing. Nevertheless, these method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::720fc556be4e5865e4cddd71e3e50aa4
Publikováno v:
2022 30th Telecommunications Forum (TELFOR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::221e89cdc3fb4a0d6455644aaaa90e51
https://doi.org/10.1109/telfor56187.2022.9983718
https://doi.org/10.1109/telfor56187.2022.9983718
Publikováno v:
2022 30th Telecommunications Forum (TELFOR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f0f4262a73be42522cb49ca9ae72a9d
https://doi.org/10.1109/telfor56187.2022.9983790
https://doi.org/10.1109/telfor56187.2022.9983790