Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Anyu Du"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 162-174 (2024)
In the field of remote sensing, change detection is a crucial study area. Deep learning has made significant strides in the study of remote sensing image change detection during the past few years. Deep learning techniques still have some drawbacks.
Externí odkaz:
https://doaj.org/article/6dc982ed4be5495d9e70243863fbc4bd
Publikováno v:
Remote Sensing, Vol 16, Iss 17, p 3184 (2024)
Semantic segmentation is currently a hot topic in remote sensing image processing. There are extensive applications in land planning and surveying. Many current studies combine Convolutional Neural Networks (CNNs), which extract local information, wi
Externí odkaz:
https://doaj.org/article/c6ef4dfdd38840038adb9705909e332b
Publikováno v:
IET Image Processing, Vol 17, Iss 2, Pp 492-504 (2023)
Abstract Owing to the renaissance of deep convolutional neural networks (CNN), salient object detection based on fully convolutional neural networks (FCNs) has attracted widespread attention. However, the scale variation of prominent objects, complex
Externí odkaz:
https://doaj.org/article/e5c6acf2abdf4d8bb197bc5ab39a1b9c
Publikováno v:
IEEE Access, Vol 10, Pp 25435-25447 (2022)
RGB-D salient object detection (SOD) usually describes two modes’ classification or regression problem, namely RGB and depth. The existing RGB-D SOD methods use depth hints to increase the detection performance, meanwhile they focus on the quality
Externí odkaz:
https://doaj.org/article/14326a683d10463aaee47e9b7cae1a77
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-17 (2021)
Abstract In recent years, the hyperspectral classification algorithm based on deep learning has received widespread attention, but the existing network models have higher model complexity and require more time consumption. In order to further improve
Externí odkaz:
https://doaj.org/article/bfbf761333724195bd8a38c83405dff5
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5741 (2023)
Insulators are widely used in various aspects of the power system and play a crucial role in ensuring the safety and stability of power transmission. Insulator detection is an important measure to guarantee the safety and stability of the transmissio
Externí odkaz:
https://doaj.org/article/3fea95df535f4f61bcaca20f91016161
Publikováno v:
IEEE Access, Vol 8, Pp 217290-217305 (2020)
In the SAR change detection algorithm based on self-supervised learning, speckle noise reduces the difference image (DI) quality. Therefore, the contrast of the DI is low, and its change area is not significant. Moreover, the preclassification algori
Externí odkaz:
https://doaj.org/article/b6a1b02ff6314b74827050a0f37a2018
Publikováno v:
IEEE Access, Vol 8, Pp 203700-203711 (2020)
At present, occlusion and appearance similarity pose severe challenges to person re-identification tasks. Although many robust deep convolutional neural networks alleviate these problems, convolutional layers with limited receptive fields cannot mode
Externí odkaz:
https://doaj.org/article/838897ba377a4f399a3588d37ad01baa
Publikováno v:
Information, Vol 13, Iss 10, p 453 (2022)
Currently, deep learning is the mainstream method to solve the problem of person reidentification. With the rapid development of neural networks in recent years, a number of neural network frameworks have emerged for it, so it is becoming more import
Externí odkaz:
https://doaj.org/article/41f9a776080c45dcbaae534c1ac8216f
Publikováno v:
Automatika, Vol 60, Iss 4, Pp 491-499 (2019)
This paper proposes an improved method for extracting NMI features. This method uses Particle Swarm Optimization in advance to optimize the two-dimensional maximum class-to-class variance (2OTSU) in advance. Afterwards, the optimized 2OUSU is introdu
Externí odkaz:
https://doaj.org/article/82e95c5793d14260b54e17b8bddffb82