Zobrazeno 1 - 10
of 176
pro vyhledávání: '"feature pyramid network (FPN)"'
Publikováno v:
Jin'gangshi yu moliao moju gongcheng, Vol 44, Iss 5, Pp 588-598 (2024)
Objectives: With the improvement of production technology, the traditional diamond particle cleanliness detection method can no longer meet the requirements of high precision, high quality and high automation in the diamond industry due to its low ef
Externí odkaz:
https://doaj.org/article/bb9a74c9d06d4de9beb6f83c31214f95
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 15583-15595 (2024)
Synthetic aperture radar (SAR) has been widely used in maritime domain awareness, especially in ship detection, due to the capability of working all-day and all-weather. In the detection of SAR ships, there are significant challenges in sea clutter,
Externí odkaz:
https://doaj.org/article/2eaf8461a86e40f5a58b954663b914f6
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12706-12719 (2024)
The complex background and coherent speckle noise in synthetic aperture radar (SAR) images presents a significant challenge for the detection and recognition of SAR small targets. For deep neural networks, the robust feature learning method and effec
Externí odkaz:
https://doaj.org/article/61a499e0747a4239b8b18287e2eee605
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7725-7737 (2024)
A dust devil is an important part of the Martian climate system, which can help us better understand scientific questions of the climate, surface–atmosphere interactions, aeolian processes, and regolith on Mars. Therefore, the automatic detection o
Externí odkaz:
https://doaj.org/article/c91fdcbef4024111b3f59cdbd7c905a9
Publikováno v:
Shipin yu jixie, Vol 39, Iss 11, Pp 131-136,151 (2023)
Objective: Accurate identification and location of paper packaging box defects. Methods: The improved network model of Faster R-CNN was applied to automatically detect box defects. The data of the training set picture was enhanced and noise was added
Externí odkaz:
https://doaj.org/article/cb2ca8f6d6084a428e5bd7964c845fb0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 9904-9915 (2023)
Synthetic aperture radar (SAR) ship detection is widely used in cutting-edge applications such as environmental protection, traffic monitoring, search, and rescue. Lightweight detection algorithms are more important for practical applications. Althou
Externí odkaz:
https://doaj.org/article/ea00d4b8d5394971976c225ab374b1f1
LWCCNet: Lightweight Remote Sensing Change Detection Network Based on Composite Convolution Operator
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8621-8631 (2023)
Change detection is a basic remote sensing image processing task in agriculture, urban planning, disaster assessment, and other fields. Fully convolutional Siamese network is currently employed as the primary solution for remote sensing change detect
Externí odkaz:
https://doaj.org/article/0de081f9ff3d4dccae01dc85e358ea44
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 7507-7517 (2023)
At present, many deep-convolution-based remote sensing image target detection methods have been developed and have achieved higher detection accuracy and faster detection rate. However, they do not perform well in the face of datasets with large targ
Externí odkaz:
https://doaj.org/article/8b31ab45dcd4423db73127f3116d9378
Publikováno v:
IEEE Access, Vol 11, Pp 85600-85614 (2023)
Spatiotemporal fusion (STF) techniques play important roles in Earth observation analysis as they enable the generation of images with high spatial and temporal resolution. However, existing STF models often fuse images from various satellites, not s
Externí odkaz:
https://doaj.org/article/7a822a37ecd6453ca749d17415fbb849
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 2142-2153 (2022)
In this article, we propose an effective siamese feature pyramid network (FPN), ForkNet, for remote sensing change detection (RSCD). We find that the siamese network structure, which is widely used for RSCD, contains only one downsampling network in
Externí odkaz:
https://doaj.org/article/d131d617b4ba4a3bae563dcd0e46713f