Zobrazeno 1 - 10
of 3 201
pro vyhledávání: '"Texture Classification"'
Publikováno v:
Image Analysis and Stereology, Vol 43, Iss 3 (2024)
Binary pattern methods play a vital role in extracting texture features. However, most of existing methods struggle to capture comprehensive and discriminative texture information. This paper aims to propose a novel multi-statistic binary pattern to
Externí odkaz:
https://doaj.org/article/a67b1c9191eb43929578000376c6a927
Publikováno v:
Vietnam Journal of Computer Science, Vol 11, Iss 02, Pp 211-239 (2024)
The categorization of texture images requires the identification and extraction of meaningful keypoints, a crucial step in ensuring the precise representation of textured images. The literature has introduced numerous descriptors in order to detect a
Externí odkaz:
https://doaj.org/article/92e3f23c27bb4f199ed17e1b615e60a0
Publikováno v:
IEEE Access, Vol 12, Pp 124183-124208 (2024)
A fast and improved scale-invariant feature transform (SIFT) image stitching algorithm is proposed based on texture classification to solve the problem of huge computational complexity. In the preprocessing stage, the phase correlation algorithm is u
Externí odkaz:
https://doaj.org/article/fc6d87268e5e4fe2a60e09c24491d0d5
Autor:
Weidan Yan, Yongsheng Dong
Publikováno v:
Mathematics, Vol 12, Iss 21, p 3432 (2024)
The local binary pattern (LBP) has been widely used for extracting texture features. However, the LBP and most of its variants tend to focus on pixel units within small neighborhoods, neglecting differences in direction and relationships among differ
Externí odkaz:
https://doaj.org/article/d6ac9c043f804810b6b7244917c8dacc
Publikováno v:
Geoderma, Vol 442, Iss , Pp 116792- (2024)
A recently developed Integral Suspension Pressure (ISP) sedimentation-based particle size analysis technique was tested as an alternative to the hydrometer method. The ISP method determines the particle size distribution using an electronic device, n
Externí odkaz:
https://doaj.org/article/90bde92e3dd34ee780f73e1acb4d2371
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
Accurate texture classification empowers robots to improve their perception and comprehension of the environment, enabling informed decision-making and appropriate responses to diverse materials and surfaces. Still, there are challenges for texture c
Externí odkaz:
https://doaj.org/article/b9ae8f388d50493ab1824ea0188d2dec
Publikováno v:
Applied Sciences, Vol 14, Iss 10, p 4011 (2024)
Texture describes the unique features of an image. Therefore, texture classification is a crucial task in computer vision. Various CNN-based deep learning methods have been developed to classify textures. During training, the deep-learning model unde
Externí odkaz:
https://doaj.org/article/d0773471370f490daeeb939e4ee5d85a
Akademický článek
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Publikováno v:
Heliyon, Vol 9, Iss 11, Pp e21366- (2023)
Art designs exhibit different principles, textures, color combinations, and creative skills for vivid thinking visualizations. Art exhibits are far from ages, periods, and creators finding their digital patterns in recent years for resurrection. Degr
Externí odkaz:
https://doaj.org/article/10c9ccd0dc8b425d8e244daf73bcb9c0
Publikováno v:
Journal of Agricultural Engineering (2023)
Two pedotransfer functions (PTFs) are available in the literature enabling the soil water retention function (WRF) to be estimated from knowledge of the soil particle-size distribution (PSD), oven-dry soil bulk density (b), and saturated soil wate
Externí odkaz:
https://doaj.org/article/2233c9afbbe44ad2853615de81fba619