Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Faming Shao"'
Publikováno v:
Remote Sensing, Vol 16, Iss 17, p 3321 (2024)
The technology for object detection in remote sensing images finds extensive applications in production and people’s lives, and improving the accuracy of image detection is a pressing need. With that goal, this paper proposes a range of improvement
Externí odkaz:
https://doaj.org/article/9bccc9d5316a44d89bd2acd180c8ef6c
Publikováno v:
Drones, Vol 8, Iss 5, p 189 (2024)
UAV remote sensing (RS) image object detection is a very valuable and challenging technology. This article discusses the importance of key features and proposes an object detection network (URSNet) based on a bidirectional multi-span feature pyramid
Externí odkaz:
https://doaj.org/article/a3fcb0bc87ba4067aa48e4019e53bab8
Publikováno v:
Remote Sensing, Vol 16, Iss 6, p 1002 (2024)
Due to the broad usage and widespread popularity of drones, the demand for a more accurate object detection algorithm for images captured by drone platforms has become increasingly urgent. This article addresses this issue by first analyzing the uniq
Externí odkaz:
https://doaj.org/article/61ce244ce09642e397171ad74f8d6469
Publikováno v:
IEEE Access, Vol 10, Pp 75971-75985 (2022)
Detecting objects in aerial images is a challenging task due to the large-scale variations and arbitrary orientations with tiny instances. A new multi-scale transformer-based aerial objects detector called MStrans is proposed in this paper to deal wi
Externí odkaz:
https://doaj.org/article/171da952524443f7bc0d1b79f71af10e
Publikováno v:
IEEE Access, Vol 10, Pp 99897-99908 (2022)
Military vehicle object detection technology in complex environments is the basis for the implementation of reconnaissance and tracking tasks for weapons and equipment, and is of great significance for information and intelligent combat. In response
Externí odkaz:
https://doaj.org/article/4cf36be3008242139dd5a69610f0787d
Publikováno v:
IEEE Access, Vol 10, Pp 100526-100539 (2022)
Object detection in remote sensing imagery is a challenging task in the field of computer vision and has high research value. To improve the classification accuracy and positioning accuracy of object detection, we propose a new multi-scale oriented o
Externí odkaz:
https://doaj.org/article/555120fccbe84cc68f968ea55ed2e5d8
MSCNet: A Framework With a Texture Enhancement Mechanism and Feature Aggregation for Crack Detection
Publikováno v:
IEEE Access, Vol 10, Pp 26127-26139 (2022)
Bridge crack is one of the critical optical and visual information to judge the health state of bridges. The bridge crack detection methods based on artificial intelligence are essential in this field, but the current approaches are not satisfactory
Externí odkaz:
https://doaj.org/article/120ff6c736f6432987a84f06473daca3
Publikováno v:
IEEE Access, Vol 10, Pp 53797-53809 (2022)
Multispectral pedestrian detection based on deep learning can provide a robust and accurate detection under different illumination conditions, which has important research significance in safety. In order to reduce the log-average miss rate of the ob
Externí odkaz:
https://doaj.org/article/3dba799acf5748b282840c3ee02ce35a
Publikováno v:
Drones, Vol 7, Iss 6, p 402 (2023)
In this paper, an object detection and recognition method based on improved YOLOv5 is proposed for application on unmanned aerial vehicle (UAV) aerial images. Firstly, we improved the traditional Gabor function to obtain Gabor convolutional kernels w
Externí odkaz:
https://doaj.org/article/7e2f8343649742609045bc4d3b161a47
Publikováno v:
IEEE Access, Vol 9, Pp 60564-60576 (2021)
The hydraulic pump plays a very important role in the safe and stable operation of the hydraulic system. Once it fails, it will cause immeasurable losses to the entire hydraulic system. But in practice, because hydraulic pump often works under strong
Externí odkaz:
https://doaj.org/article/39a79304735843d7b0435d6a28f5aad3