Zobrazeno 1 - 10
of 183
pro vyhledávání: '"Heng-Chao Li"'
Publikováno v:
IET Computer Vision, Vol 18, Iss 1, Pp 124-140 (2024)
Abstract Although low‐rank representation (LRR)‐based subspace learning has been widely applied for feature extraction in computer vision, how to enhance the discriminability of the low‐dimensional features extracted by LRR based subspace learn
Externí odkaz:
https://doaj.org/article/3bcc2b56d42d458b8ad0f988bd0d9fc1
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103814- (2024)
Annotating remote sensing images (RSIs) poses a significant challenge, primarily due to its labor-intensive nature. Semi-supervised object detection (SSOD) methods address this challenge by generating pseudo-labels for unlabeled data, assuming that a
Externí odkaz:
https://doaj.org/article/7b49068ac8c54757ab9dd8518eb04128
Publikováno v:
IET Image Processing, Vol 16, Iss 12, Pp 3258-3267 (2022)
Abstract The segmentation of building from satellite and airborne images is necessary for high‐resolution buildings maps generation and it is still challenging. On annotated pixel‐level images, trained deep convolutional neural networks (CNNs) we
Externí odkaz:
https://doaj.org/article/db438a1126294283b952dc3605347a3c
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 8974-8989 (2022)
With the development of deep learning, various convolutional neural network (CNN)-based methods have been proposed for the hyperspectral image (HSI) classification. Although most of them achieve good classification performance, there are still more m
Externí odkaz:
https://doaj.org/article/1975796509da4f3daeae4ed49b20e243
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 4414-4436 (2022)
Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI). Nonnegative matrix factorization (NMF) plays an increasingly significant role in solving th
Externí odkaz:
https://doaj.org/article/ac6a666d9f174fc0a4043929a0c70ea7
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 2667-2680 (2022)
Benefited from the rapid and sustainable development of synthetic aperture radar (SAR) sensors, change detection from SAR images has received increasing attentions over the past few years. Existing unsupervised deep learning-based methods have made g
Externí odkaz:
https://doaj.org/article/a96c28043b9941ee9afa2566e7d2f838
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 8552-8565 (2021)
As a basic research topic in the field of remote sensing, semantic segmentation of high-resolution aerial images has broad application prospects. However, most existing semantic segmentation methods usually extract multiscale features of images in a
Externí odkaz:
https://doaj.org/article/86826f6952864be58fae4adde0fb4a6b
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 9651-9666 (2021)
Bridge detection in aerial images is to determine whether a given aerial image contains one or more bridges and locate them. However, the arbitrary orientations, extreme aspect ratios, and variable backgrounds pose great challenges for bridge detecti
Externí odkaz:
https://doaj.org/article/a344060426a74b29bd230f6fcc8fc8ed
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 10748-10760 (2021)
Synthetic aperture radar (SAR) image change detection is a critical yet challenging task in the field of remote sensing image analysis. The task is nontrivial due to the following challenges: First, intrinsic speckle noise of SAR images inevitably de
Externí odkaz:
https://doaj.org/article/29c466f9b437439182c3c9d471561420
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 12557-12568 (2021)
Object detection in remote sensing imagery usually suffers from inaccurate target localization and bounding box regression uncertainty, mainly due to the varying sizes of objects and the complexity of the background. Most detectors address these chal
Externí odkaz:
https://doaj.org/article/d8eed0333ba340a1b4119e3aa11c5c12