The seven-field classification plays a key role in ophthalmology, especially in the diagnosis and treatment of diabetic retinopathy. In this paper, we designed a framework that can classify 7 fields of each eye simult...
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In this study we focus on the problem of segmentation and visualization of soft tissue structures in three-dimensional (3D) magnetic resonance (MR) imaging. We introduce a classification method which is a combination ...
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In this study we focus on the problem of segmentation and visualization of soft tissue structures in three-dimensional (3D) magnetic resonance (MR) imaging. We introduce a classification method which is a combination of a recently proposed contour detection algorithm and Haslett's contextual classification method extended to 3D. This classification method is used in the classification step of a rendering model suggested by Drebin et al. for visualizing normal and pathological tissue structures in the brain. We evaluate the combination of these two methodologies, and identify some problems which have to be solved in order to develop a clinical useful tool.
A syntax-oriented method for a map-aided analysis of structures in aerial images is proposed. First the map must be analysed in order to obtain a suitable representation of its knowledge content. A special kind of gra...
A syntax-oriented method for a map-aided analysis of structures in aerial images is proposed. First the map must be analysed in order to obtain a suitable representation of its knowledge content. A special kind of graph, a so-called image-description graph, is the result of this map analysis. The knowledge of the map, represented on different description levels, is used to control the search process during the image analysis. Based on this knowledge, expectations for attribute values of image objects are defined. Generated objects are assessed relative to the expectations of the map and the object model. A set-oriented selection method is applied to deduce the processing priority using these two assessments. Expected objects are preferably processed for building up more complex objects. Thus the map-aided analysis can be used to reduce the processing time for a verification task.
In this paper,three dimensions kinematics and kinetics simulation are discussed for hardware realization of a physical biped walking-chair *** direct and inverse close-form kinematics solution of the biped walking-cha...
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In this paper,three dimensions kinematics and kinetics simulation are discussed for hardware realization of a physical biped walking-chair *** direct and inverse close-form kinematics solution of the biped walking-chair robot is *** gaits are realized with the kinematics solution,including walking straight on level floor,going up stair,squatting down and standing *** Moment Point(ZMP)equation is analyzed considering the movement of the *** simulated biped walking-chair robot is used for mechanical design,gaits development and validation before they are tested on real robot.
This paper presents an approach to text recognition which avoids the problems of thresholding and segmentation by working directly on the grey-level image recognizing an entire word at the time. For each word a sequen...
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This paper presents an approach to text recognition which avoids the problems of thresholding and segmentation by working directly on the grey-level image recognizing an entire word at the time. For each word a sequence of grey-level feature vectors is extracted. Hidden Markov models are used to describe the single characters and the sequence of feature vectors is matched against all possible combinations of models using dynamic programming. (C) 1996 patternrecognition Society. Published by Elsevier Science Ltd.
Pedestrian detection and semantic segmentation are high potential tasks for many real-time applications. However most of the top performing approaches provide state of art results at high computational costs. In this ...
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ISBN:
(纸本)9781467388511
Pedestrian detection and semantic segmentation are high potential tasks for many real-time applications. However most of the top performing approaches provide state of art results at high computational costs. In this work we propose a fast solution for achieving state of art results for both pedestrian detection and semantic segmentation. As baseline for pedestrian detection we use sliding windows over cost efficient multiresolution filtered LUV+HOG channels. We use the same channels for classifying pixels into eight semantic classes. Using short range and long range multiresolution channel features we achieve more robust segmentation results compared to traditional codebook based approaches at much lower computational costs. The resulting segmentations are used as additional semantic channels in order to achieve a more powerful pedestrian detector. To also achieve fast pedestrian detection we employ a multiscale detection scheme based on a single flexible pedestrian model and a single image scale. The proposed solution provides competitive results on both pedestrian detection and semantic segmentation benchmarks at 8 FPS on CPU and at 15 FPS on GPU, being the fastest top performing approach.
Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them....
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Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them. In the paper, a novel color image encryption algorithm is introduced. The 24 bit planes of components R, G, and B of the color plain image are obtained and recombined into 4 compound bit planes, and this can make the three components affect each other. A four-dimensional(4D) memristive hyperchaotic system generates the pseudorandom key streams and its initial values come from the SHA 256 hash value of the color plain image. The compound bit planes and key streams are confused according to the principles of genetic recombination, then confusion and diffusion as a union are applied to the bit planes,and the color cipher image is obtained. Experimental results and security analyses demonstrate that the proposed algorithm is secure and effective so that it may be adopted for secure communication.
Microscopic halftone imagerecognition and analysis can provide quantitative evidence for printing quality control and fault diagnosis of printing devices, while halftone image segmentation is one of the significant s...
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Microscopic halftone imagerecognition and analysis can provide quantitative evidence for printing quality control and fault diagnosis of printing devices, while halftone image segmentation is one of the significant steps during the procedure. Automatic segmentation on microscopic dots by the aid of the Fuzzy C-Means (FCM) method that takes account of the fuzziness of halftone image and utilizes its color information adequately is realized. Then some examples show the technique effective and simple with better performance of noise immunity than some usual methods. In addition, the segmentation results obtained by the FCM in different color spaces are compared, which indicates that the method using the FCM in the f 1f 2f 3 color space is superior to the rest.
Pedestrian detection in a real scene is an interesting application for video surveillance systems. This paper presents our contribution to improve the work of Viola and Jones, originally designed to detect faces. This...
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ISBN:
(纸本)9781424435036
Pedestrian detection in a real scene is an interesting application for video surveillance systems. This paper presents our contribution to improve the work of Viola and Jones, originally designed to detect faces. This work uses a cascade of classifiers based on Adaboost using Haar features. It improves the learning step by including a decision tree presenting the different poses and possible occlusions. The method has been tested on real and complex sequences and has given a good detection despite occlusions and poses variation.
Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and...
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Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.
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