Results 81 to 90 of about 1,301,116 (140)
A segmentation method for lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise. [PDF]
PLoS One, 2017 Zhang W +5 more
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Spatially invariant image sequences
IEEE Transactions on Image Processing, 1992The authors define linearly additive spatially invariant image sequences and present an explicit mathematical model for describing them. In such a sequence, all objects are positionally invariant in each image of the sequence but have varying gray-scale contributions to the successive images of the sequence.
J V, Miller, J B, Farison, Y, Shin
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Image Processing for Sequences of Oceanographic Images
The Journal of Visualization and Computer Animation, 1996This paper is concemed with three main problems of image processing occuring on temporal sequences of satellite oceanographic images: approximate localization of the interesting structures on the images; segmentation or determination of the boundary of the structures; and temporal tracking of these boundaries to illustrate their evolution.
Herlin, Isabelle +2 more
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Nature, 1994
Digital imaging spectrophotometers can simultaneously measure the spectra of hundreds of features in a two-dimensional scene. While a variety of applications can be anticipated, a colorimetric analysis of mutants expressing pigmented proteins has already led to the development of efficient algorithms for optimizing combinatorial mutagenesis.
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Digital imaging spectrophotometers can simultaneously measure the spectra of hundreds of features in a two-dimensional scene. While a variety of applications can be anticipated, a colorimetric analysis of mutants expressing pigmented proteins has already led to the development of efficient algorithms for optimizing combinatorial mutagenesis.
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2021
Previous chapters have laid out the foundations of AI for us in terms of the overall training process. We have an insight into the expressive power of deep neural networks, for which we used FFN with several hidden layers of neurons which are fully connected. Before the dawn of AI, shallow FFNs with one hidden layer were used in the feature space by ML
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Previous chapters have laid out the foundations of AI for us in terms of the overall training process. We have an insight into the expressive power of deep neural networks, for which we used FFN with several hidden layers of neurons which are fully connected. Before the dawn of AI, shallow FFNs with one hidden layer were used in the feature space by ML
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Spatial Encoding – Basic Imaging Sequences
2011This chapter presents the basic techniques for generating images with magnetic resonance. First, the usage of gradients for slice selection, frequency and phase encoding is explained. The concept of k-space is introduced and imperfections of the encoding methods are demonstrated by means of the point spread function.
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From image sequence to mosaic image
SPIE Proceedings, 2001A 3D plenoptic function in the form of a mosaic image is presented in this paper. A sequence of plane images and relative cylinder panoramas are sampled original ly by a camera constrained on a line. Then, these original images are arranged in to a mosaic image by abstracting appropriate circles from the images and pasting them together.
Hanfeng Chen, Su Zhang, Feihu Qi
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1981
Although the restoration and enhancement of single images have been studied extensively [4.1], there have been very few results in the literature on the restoration and enhancement of image sequences. In Chap.3 of this book, noise reduction in image sequences is discussed in connection with interframe coding.
T. S. Huang, Y. P. Hsu
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Although the restoration and enhancement of single images have been studied extensively [4.1], there have been very few results in the literature on the restoration and enhancement of image sequences. In Chap.3 of this book, noise reduction in image sequences is discussed in connection with interframe coding.
T. S. Huang, Y. P. Hsu
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