Results 201 to 210 of about 125,098 (262)

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source

Texture Features of ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography for Predicting Programmed Death-Ligand-1 Levels in Non-Small Cell Lung Cancer. [PDF]

J Clin Med
Norikane T, Ishimura M, Mitamura K, Yamamoto Y, Arai-Okuda H, Manabe Y, Murao M, Morita R, Obata T, Tanaka K, Murota M, Kanaji N, Nishiyama Y.   +12 more
europepmc   +1 more source

A machine learning-based approach to identify peripheral artery disease using texture features from contrast-enhanced magnetic resonance imaging. [PDF]

Magn Reson Imaging
Khagi B, Belousova T, Short CM, Taylor A, Nambi V, Ballantyne CM, Bismuth J, Shah DJ, Brunner G.   +8 more
europepmc   +1 more source

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Texture features based on texture spectrum

Pattern Recognition, 1991
Abstract Texture is an important spatial feature useful for identifying objects or regions of interest in an image. This paper presents a new set of textural measures derived from the texture spectrum. The proposed features extract textural information of an image with a more complete respect of texture characteristics (in all the eight directions ...
Dong-Chen He
exaly   +2 more sources

Statistical geometrical features for texture classification [PDF]

Pattern Recognition, 1995
Abstract This paper proposes a novel set of 16 features based on the statistics of geometrical attributes of connected regions in a sequence of binary images obtained from a texture image. Systematic comparison using all the Brodatz textures shows that the new set achieves a higher correct classification rate than the well-known Statistical Gray ...
Yan Qiu Chen, Mark S Nixon
exaly   +2 more sources

Texture Browser: Feature‐based Texture Exploration

Computer Graphics Forum, 2021
AbstractTexture is a key characteristic in the definition of the physical appearance of an object and a crucial element in the creation process of 3D artists. However, retrieving a texture that matches an intended look from an image collection is difficult.
Xuejiao Luo, Leonardo Scandolo, Elmar Eisemann   +2 more
openaire   +1 more source

Textural features corresponding to textural properties

IEEE Transactions on Systems, Man, and Cybernetics, 1989
Five properties of texture, namely, coarseness, contrast, business, complexity, and texture strength, are given conceptual definitions in terms of spatial changes in intensity. These conceptual definitions are then approximated in computational forms.
Moses Amadasun, Robert King
openaire   +1 more source

Texture feature extraction

Pattern Recognition Letters, 1987
Abstract We present a new approach to texture feature extraction from a cooccurrence matrix. Computationally, the method is much faster than traditional uses of cooccurrence matrices. Using Brodatz's textures, the proposed features are evaluated and compared with those suggested by Conners et al. (1984).
Dong-Chen He, Li Wang 0002, Jean Guibert
openaire   +1 more source

Feature-preserving procedural texture

The Visual Computer, 2017
This paper presents how to synthesize a texture in a procedural way that preserves the features of the input exemplar. The exemplar is analyzed in both spatial and frequency domains to be decomposed into feature and non-feature parts. Then, the non-feature parts are reproduced as a procedural noise, whereas the features are independently synthesized ...
HyeongYeop Kang, JungHyun Han
openaire   +1 more source

Textural Features for Image Classification

IEEE Transactions on Systems, Man, and Cybernetics, 1973
Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes some easily computable textural features based on gray-tone spatial dependancies, and illustrates their application in category ...
Robert M. Haralick, Karthikeyan S. Shanmugam, Its'hak Dinstein   +2 more
openaire   +1 more source