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Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2244-2256 (2024)
Abstract Deep neural networks have seen a surge of successful methods in natural image matting. However, the overlap of foreground and background color distributions in an image is still troubling in matting. It is observed that the three color chann
Externí odkaz:
https://doaj.org/article/9d72c271d7d84f14861fcbbdaa60469d
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2461-2475 (2024)
Abstract Currently, deep learning methods for low‐light image enhancement tasks mainly focus on the illumination of images, while neglecting the problems of image noise and feature loss. To address this issue, this paper proposes a novel low‐ligh
Externí odkaz:
https://doaj.org/article/40571a22b3d6410aa9ae3960ecee65fc
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2476-2489 (2024)
Abstract Current research on apron conflict detection is often limited to the interaction between the aircraft as a whole and other objects, making it difficult to accomplish targeted identification of vulnerable and high‐cost aircraft components.
Externí odkaz:
https://doaj.org/article/400a0ff3b2a44af085c81b48115f84cd
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2291-2303 (2024)
Abstract Automatic detection of tomato leaf spot disease is essential for control and loss reduction. Traditional algorithms face challenges such as large amount of data, multiple training and heavy computation. In this study, a lightweight shared Si
Externí odkaz:
https://doaj.org/article/0e394ffd68b84a68a23905336770b6a1
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2257-2272 (2024)
Abstract In recent years, most video segmentation methods use deep CNN to process the input image, but they did not fully mine the rich intermediate predictions in spatio‐temporal space. And, the segmentation challenges such as occlusion, severe de
Externí odkaz:
https://doaj.org/article/1950ea4a50c248c18dd6f4d2c8adb354
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2215-2243 (2024)
Abstract Single image super‐resolution (SISR) is a promising research direction in computer vision and image processing for improving the visual perception of low‐quality images. In recent years, deep learning algorithms have driven tremendous de
Externí odkaz:
https://doaj.org/article/0b7b7ae331044427be79d8cd5e4cbd42
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2357-2371 (2024)
Abstract Lesion segmentation is a fundamental task in medical image processing, often facing the challenge of subtle lesions. It is important to detect these lesions, even though they can be difficult to identify. Convolutional neural networks, an ef
Externí odkaz:
https://doaj.org/article/189413db5c0f491ba44c1155a981deef
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2273-2290 (2024)
Abstract In order to solve the related problems of detection and tracking of shallow marine organisms, this paper designs a YOLO v5 multi‐target detection and tracking algorithm with attention mechanism. When working underwater, the authors usually
Externí odkaz:
https://doaj.org/article/972f7d37fd8344f39ecf09bdb9763dc7
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2318-2328 (2024)
Abstract A lightweight fruit detection algorithm is important to ensure real‐time detection on low‐power computing devices while maintaining detection accuracy. In addition, the fruit detection algorithm is also faced with some environmental fact
Externí odkaz:
https://doaj.org/article/585721974f2040d69d7ec41aeb6a9c4b
Publikováno v:
IET Image Processing, Vol 18, Iss 9, Pp 2329-2345 (2024)
Abstract At present, the multi‐object tracking method based on transformer generally uses its powerful self‐attention mechanism and global modelling ability to improve the accuracy of object tracking. However, most existing methods excessively re
Externí odkaz:
https://doaj.org/article/5a90ff3171a34e3ab1f9df2d2d84ebdd