Various technologies have been used to protect the copyrights of digital contents from illegal or unintentional attacks. Watermarking methods protect digital contents by embedding a watermark message into them. Howeve...
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ISBN:
(纸本)9783540743767
Various technologies have been used to protect the copyrights of digital contents from illegal or unintentional attacks. Watermarking methods protect digital contents by embedding a watermark message into them. However, since conventional watermarking algorithms change original digital contents to embed digital watermarks using various embedding methods, they result in the degradation of digital contents and decrease the fidelity of digital contents. A fingerprinting technique can be also used for protecting digital contents. However this method may have high computational complexity to generate unique features for digital contents. In order to provide the excellent fidelity, the proposed technique distributes original digital contents without any change like fingerprinting technique and just generates the content-associated information, which is combined wavelet coefficients with copyright message and used to extract copyright message afterward. Experimental results show that the proposed method outperforms an existing method for various signalprocessing attacks.
Neurotransmitter fields differ from neural fields in the underlying principle that the state variables are not the neuron action potentials, but the chemical concentration of neurotransmitters in the extracellular spa...
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ISBN:
(纸本)9783540746935
Neurotransmitter fields differ from neural fields in the underlying principle that the state variables are not the neuron action potentials, but the chemical concentration of neurotransmitters in the extracellular space. The dendritic arbor of a new electro-chemical neuron model performs a computation on the surrounding field of neurotransmitters. These fields may represent quantities such as position, force, momentum, or energy. Any computation performed by a neural network has a direct analog to a neurotransmitter field computation. While models that use action potentials as state variables may form associations using matrix operations on a large vector of neuron outputs, the neurotransmitter state model makes it possible for a small number of neurons, even a single neuron, to establish an association between an arbitrary pattern in the input field and an arbitrary output pattern. A single layer of neurons, in effect, performs the computation of a two-layer neural network.
Three dimensional Electron Microscopy (EM) and in particular single particle reconstruction using cryo-EM, has rapidly advanced over recent years, such that increasingly several macromolecular complexes can be resolve...
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ISBN:
(纸本)9781424406715
Three dimensional Electron Microscopy (EM) and in particular single particle reconstruction using cryo-EM, has rapidly advanced over recent years, such that increasingly several macromolecular complexes can be resolved at sub-nanometer resolution (6-10 angstrom). This paper reviews some of the main volumetric image and geometric post-processing steps once a three dimensional EM map (henceforth a 3D map) has been reconstructed from single particle Cryo-EM, as essential steps in an enhanced and automated computational structure interpretation pipeline. In particular the paper addresses automated filtering, critical point calculations, symmetric and non-symmetric molecular domain segmentation, and protein secondary structure (alpha-helices and beta-sheets) elucidation from 3D maps.
The following topics are dealt with: computationalintelligence; security of data; defense application; military computing; imageprocessing and evolutionary computation
The following topics are dealt with: computationalintelligence; security of data; defense application; military computing; imageprocessing and evolutionary computation
This paper describes a novel real-time technique to determine horizontal human face pose from a video color sequence. The idea underlying this technique is that when head is at an arbitrary pose to the right or left, ...
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ISBN:
(纸本)9783540771289
This paper describes a novel real-time technique to determine horizontal human face pose from a video color sequence. The idea underlying this technique is that when head is at an arbitrary pose to the right or left, there are significant relationships between the distance from center of both pupils to head center, and the distance between both pupils. From these distances, we compute a ratio known as "horizontal ratio". This ratio, besides being advantageous in the sense that it reduces the dependency on facial features tracking accuracy and robust to noise, is actually the quantity that is used to determine the horizontal human face pose. The technique is simple, computational cheap and requires only information that is usually retrievable from a face and facial feature tracker.
Filtering is a preliminary process in many medical imageprocessing applications. It is aiming at reducing noise in images, and any post-processing tasks may benefit from the reduction of noise. The major two noises i...
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ISBN:
(纸本)9783540741701
Filtering is a preliminary process in many medical imageprocessing applications. It is aiming at reducing noise in images, and any post-processing tasks may benefit from the reduction of noise. The major two noises in computed radiography (CR) images are Gaussian white noise and Poisson noise. By considering both the characteristics of CR images and the statistical features of wavelet transformed coefficients, an efficient spatial adaptive filtering algorithm, which is based on statistical model of local dependency of CR image wavelet coefficients and the approximate minimum mean squared error (MMSE) estimation, is proposed to decrease the Gaussian white noise in computed images. The process is computational cost saving, and the denoising experiments show the algorithm outperforms other approaches in peak-signal-to-noise ratio (PSNR).
The following topics are dealt with: coding theory; speech and audio signalprocessing; wireless personal communication; system on chip; SoC; direct of arrrival estimation; image enhancement and filtering; CDMA; TDMA;...
The following topics are dealt with: coding theory; speech and audio signalprocessing; wireless personal communication; system on chip; SoC; direct of arrrival estimation; image enhancement and filtering; CDMA; TDMA; OFDM; radar tracking; radar detection; image denoising; feature extraction and detection; information theory; spectral estimation; image segmentation; wireless ad hoc and sensor network; FPGA; embedded system; parameter estimation; channel estimation; image coding; analog circuits; digital filters; filter bank; video coding and transmission; MIMO communication; motion estimation; multimedia management; computationalintelligence; image fusion; communication protocols; face detection; PCA; ICA; SVD; optical-signalprocessing; radar signalprocessing.
This paper introduces the notion of the variadic neural network (VNN). The inputs to a variadic network are an arbitrary-length list of n-tuples of real numbers, where n is fixed. In contrast to a recurrent network wh...
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ISBN:
(纸本)9783540746898
This paper introduces the notion of the variadic neural network (VNN). The inputs to a variadic network are an arbitrary-length list of n-tuples of real numbers, where n is fixed. In contrast to a recurrent network which processes a list sequentially, typically being affected more by more recent list elements, a variadic network processes the list simultaneously and is affected equally by all list elements. Formally speaking, the network can be seen as instantiating a function on a multiset along with a member of that multiset. I describe a simple implementation of a variadic network architecture, the multi-layer variadic perceptron (MLVP), and present experimental results showing that such a network can learn various variadic functions by back-propagation.
Surveillance is one of the promising applications to which smart camera motes forming a vision-enabled network can add increasing levels of intelligence. We see a high degree of in-node processing in combination with ...
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ISBN:
(纸本)9781595936387
Surveillance is one of the promising applications to which smart camera motes forming a vision-enabled network can add increasing levels of intelligence. We see a high degree of in-node processing in combination with distributed reasoning algorithms as the key enablers for such intelligent surveillance systems. To put these systems into practice still requires a considerable amount of research ranging from mote architectures, pixel-processing algorithms, up to distributed reasoning engines. This paper introduces MeshEye, an energy-efficient smart camera mote architecture that has been designed with intelligent surveillance as the target application in mind. Special attention is given to MeshEye's unique vision system: a low-resolution stereo vision system continuously determines position, range, and size of moving objects entering its field of view. This information triggers a color camera module to acquire a high-resolution image sub-array containing the object, which can be efficiently processed in subsequent stages. It offers reduced complexity, response time, and power consumption over conventional solutions. Basic vision algorithms for object detection, acquisition, and tracking are described and illustrated on real-world data. The paper also presents a basic power model that estimates lifetime of our smart camera mote in battery-powered operation for intelligent surveillance event processing.
In this article, we analyze the morphometric measures of dendrite spines of mice derived from electron tomography images for different spine types based on pre-assigned categories. The morphometric measures we conside...
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ISBN:
(纸本)9789531841160
In this article, we analyze the morphometric measures of dendrite spines of mice derived from electron tomography images for different spine types based on pre-assigned categories. The morphometric measures we consider include the metric distance, volume, surface area, and length of dendrite spines of mice. The question of interest is how these morphometric measures differ by condition of mice;and how the metric distance relates to volume, surface area, length, and condition of mice. The Large Deformation Diffeomorphic Metric Mapping algorithm is the tool we use to obtain the metric distances that quantize the morphometry of binary images of dendrite spines with respect to a template spine. We demonstrate that for the values not adjusted for scale metric distances and other morphometric measures are significantly different between the conditions. The morphometric measures (rather than the mice condition) explain almost all the variation in metric distances. Since size (or scale) dominates the other variables in variation, we adjust metric distances and other morphometric measures for scale. We demonstrate that the scaled metric distances and other scaled morphometric variables still differ for condition, and scaled metric distances depend most significantly on scaled morphometric measures. The methodology used is also valid for morphometric measures of other organs or tissues and metric distances other than LDDMM.
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