Zobrazeno 1 - 10
of 624
pro vyhledávání: '"complex background"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Distributed optical fiber sensor (DAS) is an emerging acquisition technique and has begun to be widely applied in seismic exploration owing to its advantages in acquisition and deployment. Nonetheless, DAS record has a low signal-to-noise ra
Externí odkaz:
https://doaj.org/article/83e0912cdbce438a8ee788afc209a699
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2434-2448 (2024)
Abstract Defect detection in complex background is a critical issue. To address this issue, this paper proposes the mixture attention mechanism cascade network, in which the new channel attention network is linked with the spatial attention network t
Externí odkaz:
https://doaj.org/article/a80ad2e00dcd4a8e89f57fe1b65cc0fb
Autor:
Ting Zhang, Jikui Zhu, Fengkui Zhang, Shijie Zhao, Wei Liu, Ruohong He, Hongqiang Dong, Qingqing Hong, Changwei Tan, Ping Li
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
BackgroundCotton pests have a major impact on cotton quality and yield during cotton production and cultivation. With the rapid development of agricultural intelligence, the accurate classification of cotton pests is a key factor in realizing the pre
Externí odkaz:
https://doaj.org/article/1e939c70342c4c2d97c0805e10fa223f
Publikováno v:
IEEE Access, Vol 12, Pp 128677-128693 (2024)
Aiming at the challenges of low detection accuracy, susceptibility to complex background interference, difficulty in detecting small objects, and multi-scale object issues in aerial images, our proposed an improved YOLOv8-based object detection algor
Externí odkaz:
https://doaj.org/article/3d7a666a09944dbd99679862c89f2f15
Publikováno v:
IEEE Access, Vol 12, Pp 45026-45043 (2024)
Infrared object detection holds significant importance in automatic target search and tracking system under complex background. The conventional structural tensor models have not harnessed the full potential of spatio-temporal domain information in s
Externí odkaz:
https://doaj.org/article/644da468f8e740e09520c4ae7dae2436
Publikováno v:
IEEE Access, Vol 12, Pp 32870-32880 (2024)
The detection of pavement diseases is an important and basic link in the road maintenance process. Many methods based on deep learning have been applied. However, these methods are not accurate enough and cannot accurately identify defects in complex
Externí odkaz:
https://doaj.org/article/9527c674c8fd49a496c5549dd30be290
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4845-4858 (2024)
With the rapid development of synthetic aperture radar (SAR) technology, SAR remote sensing has a wide range of applications in fields, such as marine surveillance and sea rescue. Currently, the SAR ship detection model based on deep learning suffers
Externí odkaz:
https://doaj.org/article/33662b69d6aa4c8fb210d6ac0dae066a
Publikováno v:
IEEE Access, Vol 12, Pp 14532-14546 (2024)
Insulators play a pivotal role in power transmission lines, and the timely detection of defects in insulators is crucial to prevent potentially catastrophic consequences in terms of human lives and property. This paper proposes an insulator defect de
Externí odkaz:
https://doaj.org/article/babded47b0fc47409b7087581b7686bf
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1535-1549 (2024)
Existing convolutional neural network (CNN) based methods usually tend to ignore the contextual information for citrus tree canopy segmentation. Although popular transformer models are helpful in extracting global semantic information, they ignore th
Externí odkaz:
https://doaj.org/article/a5d02096f4594a4f8ce2bb756a3fb2e1
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Maize leaf diseases significantly impact yield and quality. However, recognizing these diseases from images taken in natural environments is challenging due to complex backgrounds and high similarity of disease spots between classes.This study propos
Externí odkaz:
https://doaj.org/article/693f32cfbf8f4050b13586dd9ea0abf4