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"abstract": "According to the principle of electrostatic precipitation, the paper analyzes the appearance reason of anti-corona when higher resistivity powder is removed. Electrostatic precipitation can work with high efficiency and energy-saving by using new technique of power supply to avoid anti-corona. As well as it can reduce the thickness of powder by technique rebuilding for the electric control power supply, each electric field is finely controlled with different power supply style. The paper gives a project of technique rebuild for energy-saving and reduction of powder discharged. It will have a widespread application as well as a broad prospect to be implemented.",
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"title": "2010 International Forum on Information Technology and Applications (IFITA 2010)",
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"title": "Experimental Studies on Electric Field Characteristics for a Wider Electrode Spacing and Longer Discharge Spine Electrode Base on CAT",
"normalizedTitle": "Experimental Studies on Electric Field Characteristics for a Wider Electrode Spacing and Longer Discharge Spine Electrode Base on CAT",
"abstract": "In other to analyze the regular pattern of the electric characteristic with the parametric variation of the electrode configuration, experiments of the I-V characteristic and current density of both nine kinds of conventional corona wires and three types of the longer discharge spine electrode are respectively tested by means of CAT under the two conditions that different types of corona electrodes are placed in the same electrode spacing and the same corona electrode are placed in different sizes of the electrode spacing. From the analysis and comparison of finished experimental results we can confirm that the superiority of applying the longer discharge spine electrode to the wider electrode spacing electrostatic precipitator is obvious, and this research provides a theoretical basis for further improving the collecting efficiency of the electrostatic precipitator.",
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{
"abstractType": "Regular",
"content": "In other to analyze the regular pattern of the electric characteristic with the parametric variation of the electrode configuration, experiments of the I-V characteristic and current density of both nine kinds of conventional corona wires and three types of the longer discharge spine electrode are respectively tested by means of CAT under the two conditions that different types of corona electrodes are placed in the same electrode spacing and the same corona electrode are placed in different sizes of the electrode spacing. From the analysis and comparison of finished experimental results we can confirm that the superiority of applying the longer discharge spine electrode to the wider electrode spacing electrostatic precipitator is obvious, and this research provides a theoretical basis for further improving the collecting efficiency of the electrostatic precipitator.",
"__typename": "ArticleAbstractType"
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"normalizedAbstract": "In other to analyze the regular pattern of the electric characteristic with the parametric variation of the electrode configuration, experiments of the I-V characteristic and current density of both nine kinds of conventional corona wires and three types of the longer discharge spine electrode are respectively tested by means of CAT under the two conditions that different types of corona electrodes are placed in the same electrode spacing and the same corona electrode are placed in different sizes of the electrode spacing. From the analysis and comparison of finished experimental results we can confirm that the superiority of applying the longer discharge spine electrode to the wider electrode spacing electrostatic precipitator is obvious, and this research provides a theoretical basis for further improving the collecting efficiency of the electrostatic precipitator.",
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"Electrodes",
"Electrostatic Precipitators",
"Electric Field Characteristics",
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{
"affiliation": null,
"fullName": "Lin Hui",
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{
"affiliation": null,
"fullName": "Huang Chao",
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"fullName": "Ma Xiuqin",
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"fullName": "Wang Fei",
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{
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"fullName": "Yang Zengjun",
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"surname": "Zengjun",
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"proceeding": {
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"title": "2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)",
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"abstract": "In this paper, a new technique to measure daily human body motion without using cameras and video images is presented. The change in the electric potential of the human body that is caused by the daily performance induces an electrostatic induction current in the electrode placed at a distance of a few meters from the human body. Using this technology, I have developed an effective non-contact technique for the detection of human daily performance by detecting the change in this human-generated body charge. This technique based on the detection of an electrostatic induction current of the order of approximately sub-picoamperes flowing through an electrode that is placed at a distance of 5 m from the subject. It is shown that the characteristics of the individual are included in walking motion, sitting on a chair and retiring motion. This technique effectively explains the behavior of the waveform of the electrostatic induction current flowing through a given measurement electrode through a capacitance model of the human body.",
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{
"abstractType": "Regular",
"content": "In this paper, a new technique to measure daily human body motion without using cameras and video images is presented. The change in the electric potential of the human body that is caused by the daily performance induces an electrostatic induction current in the electrode placed at a distance of a few meters from the human body. Using this technology, I have developed an effective non-contact technique for the detection of human daily performance by detecting the change in this human-generated body charge. This technique based on the detection of an electrostatic induction current of the order of approximately sub-picoamperes flowing through an electrode that is placed at a distance of 5 m from the subject. It is shown that the characteristics of the individual are included in walking motion, sitting on a chair and retiring motion. This technique effectively explains the behavior of the waveform of the electrostatic induction current flowing through a given measurement electrode through a capacitance model of the human body.",
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"normalizedAbstract": "In this paper, a new technique to measure daily human body motion without using cameras and video images is presented. The change in the electric potential of the human body that is caused by the daily performance induces an electrostatic induction current in the electrode placed at a distance of a few meters from the human body. Using this technology, I have developed an effective non-contact technique for the detection of human daily performance by detecting the change in this human-generated body charge. This technique based on the detection of an electrostatic induction current of the order of approximately sub-picoamperes flowing through an electrode that is placed at a distance of 5 m from the subject. It is shown that the characteristics of the individual are included in walking motion, sitting on a chair and retiring motion. This technique effectively explains the behavior of the waveform of the electrostatic induction current flowing through a given measurement electrode through a capacitance model of the human body.",
"fno": "08279698",
"keywords": [
"Capacitance",
"Data Visualisation",
"Electric Potential",
"Electrodes",
"Electromagnetic Induction",
"Electrostatics",
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"Signal Detection",
"Electrostatic Induction Current",
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"authors": [
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"affiliation": "Kindai University, Faculty of Engineering, Department of Electronic Engineering and Computer Science, Higashi-Hiroshima, Japan",
"fullName": "Koichi Kurita",
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"abstract": "In order to improve collecting efficiency of wet electsostatic precipitation a new polar matching system is presented. Based on Gauss Theorem and image charge method the mathematical model is established for calculating electric field intensity distribution of the new polar matching system. The results show that the electric field intensity gets homogeneous at the polar plate when polar space is at suitable value. The electric field intensity of the new polar matching system meets Gauss Theorem well at arbitrary section. The structural characteristics of electric polar is affected by many factors, such as: geometrical parameters, dust concentration distribution and applied voltage. The new polar matching system has the advantage of even electric field intensity when the electric polars and discharge nozzle-electrodes are on small distance. The calculated results accord with the actual distribution law of electrostatic precipitator. It can be directly used for the design of wet electrostatic precipitator.",
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"abstract": "Motions can occur over both short and long time scales. We introduce motion denoising, which treats short-term changes as noise, long-term changes as signal, and re-renders a video to reveal the underlying long-term events. We demonstrate motion denoising for time-lapse videos. One of the characteristics of traditional time-lapse imagery is stylized jerkiness, where short-term changes in the scene appear as small and annoying jitters in the video, often obfuscating the underlying temporal events of interest. We apply motion denoising for resynthesizing time-lapse videos showing the long-term evolution of a scene with jerky short-term changes removed. We show that existing filtering approaches are often incapable of achieving this task, and present a novel computational approach to denoise motion without explicit motion analysis. We demonstrate promising experimental results on a set of challenging time-lapse sequences.",
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"abstract": "State of the art movie restoration methods either estimate motion and filter out the trajectories, or compensate the motion by an optical flow estimate and then filter out the compensated movie. Now, the motion estimation problem is ill posed. This fact is known as the aperture problem: trajectories are ambiguous since they could coincide with any promenade in the space-time isophote surface. In this paper, we try to show that, for denoising, the aperture problem can be taken advantage of. Indeed, by the aperture problem, many pixels in the neighboring frames are similar to the current pixel one wishes to denoise. Thus, denoising by an averaging process can use many more pixels than just the ones on a single trajectory. This observation leads to use for movies a recently introduced image denoising method, the NL-means algorithm. This static 3D algorithm outperforms motion compensated algorithms, as it does not lose movie details. It involves the whole movie isophote and not just a trajectory.",
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"content": "State of the art movie restoration methods either estimate motion and filter out the trajectories, or compensate the motion by an optical flow estimate and then filter out the compensated movie. Now, the motion estimation problem is ill posed. This fact is known as the aperture problem: trajectories are ambiguous since they could coincide with any promenade in the space-time isophote surface. In this paper, we try to show that, for denoising, the aperture problem can be taken advantage of. Indeed, by the aperture problem, many pixels in the neighboring frames are similar to the current pixel one wishes to denoise. Thus, denoising by an averaging process can use many more pixels than just the ones on a single trajectory. This observation leads to use for movies a recently introduced image denoising method, the NL-means algorithm. This static 3D algorithm outperforms motion compensated algorithms, as it does not lose movie details. It involves the whole movie isophote and not just a trajectory.",
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"abstract": "Human visual system can identify larger defects taking place on the woven fabric. But it is very difficult to classify and identify the small fabric defects by a human inspector. In the textile industries the defect detection by a human inspector affects the production tremendously. Thus this paper gives a solution of this problem by developing an automatic fabric defect detection system, based on the computer vision. The sub image based PCA method is applied for the extraction of the feature from the training and test fabric images and the multi-class SVM classifier is used for carrying out the classification task. The method is tested on the standard TILDA database of fabric defect and a success rate of 96.36% is achieved.",
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"title": "Modeling the Shear Stiffness of Worsted Fabrics Using Soft Computing Techniques",
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"abstract": "The soft computing technique is used to model the relationship between the yarn properties, fabric parameters and shear stiffness of worsted fabrics. At first, the yarn properties and fabric parameters are selected by utilizing an input variable selection method. The first part of this method takes the human knowledge on the shear stiffness of fabrics into account. The second part utilizes a data sensitivity criterion based on a distance method. Then, the artificial neural network model of the relationship between the yarn properties, fabric parameters and shear stiffness of fabrics is established. The results show that the artificial neural network model yields accurate prediction and a reasonably good artificial neural network model can be achieved with relatively few data points by integrated with the input variable selecting method developed in this research.",
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{
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"content": "The soft computing technique is used to model the relationship between the yarn properties, fabric parameters and shear stiffness of worsted fabrics. At first, the yarn properties and fabric parameters are selected by utilizing an input variable selection method. The first part of this method takes the human knowledge on the shear stiffness of fabrics into account. The second part utilizes a data sensitivity criterion based on a distance method. Then, the artificial neural network model of the relationship between the yarn properties, fabric parameters and shear stiffness of fabrics is established. The results show that the artificial neural network model yields accurate prediction and a reasonably good artificial neural network model can be achieved with relatively few data points by integrated with the input variable selecting method developed in this research.",
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"normalizedAbstract": "The soft computing technique is used to model the relationship between the yarn properties, fabric parameters and shear stiffness of worsted fabrics. At first, the yarn properties and fabric parameters are selected by utilizing an input variable selection method. The first part of this method takes the human knowledge on the shear stiffness of fabrics into account. The second part utilizes a data sensitivity criterion based on a distance method. Then, the artificial neural network model of the relationship between the yarn properties, fabric parameters and shear stiffness of fabrics is established. The results show that the artificial neural network model yields accurate prediction and a reasonably good artificial neural network model can be achieved with relatively few data points by integrated with the input variable selecting method developed in this research.",
"fno": "04667970",
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"title": "Fabrics Capable of Capacitive Energy Storage",
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"abstract": "Flexible and lightweight fabric supercapacitors were seamlessly integrated into \"smart\" garments as an energy source. The electrochemical behavior of porous carbons applied with a traditional printmaking technique (screen printing) onto woven cotton and polyester fabrics was studied in non-toxic, non-flammable aqueous electrolytes. The porous structure of fabrics makes them ideal for supercapacitor applications that need porous films for ion transfer between electrodes. Electrodes derived from activated carbon (YP17) showed a high specific capacitance of 91 F/g on cotton and 85 F/g on polyester (i.e., ~0.43 F/cm2). Replacing conventional activated carbon with high surface area titanium carbidederived carbon (TiC-CDC) and adding highly conductive carbon onions, the capacitance can be improved to 160 F/g.",
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"content": "Flexible and lightweight fabric supercapacitors were seamlessly integrated into \"smart\" garments as an energy source. The electrochemical behavior of porous carbons applied with a traditional printmaking technique (screen printing) onto woven cotton and polyester fabrics was studied in non-toxic, non-flammable aqueous electrolytes. The porous structure of fabrics makes them ideal for supercapacitor applications that need porous films for ion transfer between electrodes. Electrodes derived from activated carbon (YP17) showed a high specific capacitance of 91 F/g on cotton and 85 F/g on polyester (i.e., ~0.43 F/cm2). Replacing conventional activated carbon with high surface area titanium carbidederived carbon (TiC-CDC) and adding highly conductive carbon onions, the capacitance can be improved to 160 F/g.",
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"abstract": "Many machines vision-based real-time detecting system are designed for the textile industry, almost all the textile factories will inspect the defects to ensure the quality of their products. At present, many defect detection methods have been proposed, the shortcomings of these algorithms are that their false alarms are too high. To solve this problem, we propose a Roberts cross (RC) combined with mathematical morphology approach (RCMM) for fabric defect detection. First, the mean filter is applied to preprocess the fabric images acquired from the industry. Then the RC is used to detect the edge of the images, and the inaccurate binary result can be achieved. Finally, the mathematical morphology approach is used to reduce the effects of noise and illumination on the test results, and the defects can be located. The experimental results show that the proposed RCMM algorithm can achieve 91.95% F1 index on woven fabrics with solid colors and jeans, and it also gets better defect detection performance for fabrics with complex texture background.",
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"content": "Many machines vision-based real-time detecting system are designed for the textile industry, almost all the textile factories will inspect the defects to ensure the quality of their products. At present, many defect detection methods have been proposed, the shortcomings of these algorithms are that their false alarms are too high. To solve this problem, we propose a Roberts cross (RC) combined with mathematical morphology approach (RCMM) for fabric defect detection. First, the mean filter is applied to preprocess the fabric images acquired from the industry. Then the RC is used to detect the edge of the images, and the inaccurate binary result can be achieved. Finally, the mathematical morphology approach is used to reduce the effects of noise and illumination on the test results, and the defects can be located. The experimental results show that the proposed RCMM algorithm can achieve 91.95% F1 index on woven fabrics with solid colors and jeans, and it also gets better defect detection performance for fabrics with complex texture background.",
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"affiliation": "Soochow University",
"fullName": "Miao Guan",
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"title": "Evaluation of Depth of Field for depth perception in DVR",
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"abstract": "In this paper we present a user study on the use of Depth of Field for depth perception in Direct Volume Rendering. Direct Volume Rendering with Phong shading and perspective projection is used as the baseline. Depth of Field is then added to see its impact on the correct perception of ordinal depth. Accuracy and response time are used as the metrics to evaluate the usefulness of Depth of Field. The onsite user study has two parts: static and dynamic. Eye tracking is used to monitor the gaze of the subjects. From our results we see that though Depth of Field does not act as a proper depth cue in all conditions, it can be used to reinforce the perception of which feature is in front of the other. The best results (high accuracy & fast response time) for correct perception of ordinal depth occurs when the front feature (out of the two features users were to choose from) is in focus and perspective projection is used.",
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"abstract": "Depth ordering is instrumental for understanding the 3D geometry of an image. Humans are surprisingly good at depth ordering even with abstract 2D line drawings. In this paper we propose a learning-based framework for depth ordering inference. Boundary and junction characteristics are important clues for this task, and we have developed new features based on these attributes. Although each feature individually can produce reasonable depth ordering results, each still has limitations, and we can achieve better performance by combining them. In practice, local depth ordering inferences can be contradictory. Therefore, we propose a Markov Random Field model with terms that are more global than previous work, and use graph optimization to encourage a globally consistent ordering. In addition, to produce better object segmentation for the task of depth ordering, we propose to explicitly enforce closed loops and long edges for the occlusion boundary detection. We collect a new depth-order dataset for this problem, including more than a thousand human-labeled images with various daily objects and configurations. The proposed algorithm shows promising performance over conventional methods on both synthetic and real scenes.",
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"abstract": "Texture analysis is important in 2D image classification, recognition, segmentation and detection. Although a significant amount of work has been done on 2D image data analysis, techniques for analyzing 3D volume data such as 3D solid textures have not been investigated sufficiently. In this research, we have extended the well-known Laws' texture energy approach to handle 3D solid textures. In our approach, the Laws' texture kernels are convolved together to generate three dimensional masks (3times3times3) while traditional approaches use 2D masks (3times3). The extended 3D Laws' convolution masks make it possible to analyze 3D solid texture databases. Our preliminary experiment shows that the 3D masks are capable of extracting shape features directly from 3D solid textures, although traditional techniques indirectly extract shape features from a sequence of 2D images which are sliced from 3D solid textures. The 3D mask can be used for various 3D solid texture analysis techniques including similarity retrieval, classification, recognition, and segmentation",
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"fullName": "Motofumi T. Suzuki",
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"abstract": "This paper proposes a novel photometric stereo solution to jointly estimate surface normals and scattering parameters from a globally planar, homogeneous, translucent object. Similar to classic photometric stereo, our method only requires as few as three observations of the translucent object under directional lighting. Naively applying classic photometric stereo results in blurred photometric normals. We develop a novel blind deconvolution algorithm based on inverse rendering for recovering the sharp surface normals and the material properties. We demonstrate our method on a variety of translucent objects.",
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"abstract": "This paper proposes a novel flow estimation method with a particle filter based on a Helmholtz decomposition theorem. The proposed method extends a model of the Helmholtz decomposition theorem and enables the decomposition of flows into rotational, divergent, and translational components. From the extended model, the proposed method defines a state transition model and an observation model of the particle filter. Furthermore, the proposed method derives an observation density of the particle filter from an energy function based on the Helmholtz decomposition theorem. By utilizing these novel approaches, the proposed method provides a solution to the problem in the traditional ones of not being able to realize an effective flow estimation with the particle filter based on rotation, divergence, and translation, which are important geometric features. Consequently, the proposed method can accurately estimate the flows.",
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"abstract": "Helmholtz equation is a special kind of elliptic partial differential equation. Solving Helmholtz equation is often needed in many scientific and engineering problems. The efficient approach to solving Helmholtz equation is through using Fast Fourier Transform (FFT). In practice, boundary conditions must be considered, and several discrete Fourier transforms such as Discrete Sine and Cosine Transforms (DST, DCT) are needed for solving problems with different boundary conditions. Nowadays, with the development of Compute Unified Device Architecture (CUDA) technology in recent years, many researchers use Graphics Processing Units (GPUs) to accelerate their programs. In view of the importance of FFT, NVIDIA officially provides the library cuFFT, but it does not include the calculation of DST and DCT, which brings inconvenience to users. In this paper, we present cuHelmholtz which is designed and implemented based on CUDA. It can be used to compute several kinds of three-dimensional DST and DCT, and to solve three-dimensional Helmholtz equations with various boundary conditions. The experimental results show that compared with FISHPACK, a FORTRAN software package which can be used to solve three-dimensional Helmholtz equation, we achieve about 10x to 30x speedup.",
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"abstract": "Building home assistant robots has long been a goal for vision and robotics researchers. To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable. Existing environments achieve these requirements for robotics simulation with different levels of simplification and focus. We take one step further in constructing an environment that supports household tasks for training robot learning algorithm. Our work, SAPIEN, is a realistic and physics-rich simulated environment that hosts a large-scale set of articulated objects. SAPIEN enables various robotic vision and interaction tasks that require detailed part-level understanding.We evaluate state-of-the-art vision algorithms for part detection and motion attribute recognition as well as demonstrate robotic interaction tasks using heuristic approaches and reinforcement learning algorithms. We hope that SAPIEN will open research directions yet to be explored, including learning cognition through interaction, part motion discovery, and construction of robotics-ready simulated game environment.",
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"content": "Building home assistant robots has long been a goal for vision and robotics researchers. To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable. Existing environments achieve these requirements for robotics simulation with different levels of simplification and focus. We take one step further in constructing an environment that supports household tasks for training robot learning algorithm. Our work, SAPIEN, is a realistic and physics-rich simulated environment that hosts a large-scale set of articulated objects. SAPIEN enables various robotic vision and interaction tasks that require detailed part-level understanding.We evaluate state-of-the-art vision algorithms for part detection and motion attribute recognition as well as demonstrate robotic interaction tasks using heuristic approaches and reinforcement learning algorithms. We hope that SAPIEN will open research directions yet to be explored, including learning cognition through interaction, part motion discovery, and construction of robotics-ready simulated game environment.",
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"affiliation": "UC San Diego",
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"abstract": "The current paper proposes a new parametric local color correction technique. Initially, several color transfer functions are computed from the output of the mean shift color segmentation algorithm. Secondly, color influence maps are calculated. Finally, the contribution of every color transfer function is merged using the weights from the color influence maps. The proposed approach is compared with both global and local color correction approaches. Results show that our method outperforms the technique ranked first in a recent performance evaluation on this topic. Moreover, the proposed approach is computed in about one tenth of the time.",
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"title": "2016 IEEE Trustcom/BigDataSE/ISPA",
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"abstract": "The purpose of this paper is to improve the automatic collision avoidance procedure of two ships stipulated in open sea areas without the disturbances of wind, wave and current, which is achieved by altering course based on ship dynamic domain. As the rapid increase in the study of ship collision risk index (CRI) and automatic collision avoidance decision-making for ships, the decision-making process is fully recognized. In this paper, the model of ship dynamic domain are adopted and a series of simulation studies are made. The safe distance of approach (SDA) is determined by ship dynamic domain. Then ship automatic collision avoidance procedure is established to controlling course alteration for collision avoidance. Experimental results show that ship dynamic domain is suitable to collision avoidance. The key factor that leads to the in validation is the CRI and course alteration. Based on the seagoing experience and simulation, the decision-making for collision avoidance in three encounter situations is accurate enough for this application. The results provide a reference that compute and display the ship parameters fast and accurately to decision-making process of ship collision avoidance.",
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"content": "The purpose of this paper is to improve the automatic collision avoidance procedure of two ships stipulated in open sea areas without the disturbances of wind, wave and current, which is achieved by altering course based on ship dynamic domain. As the rapid increase in the study of ship collision risk index (CRI) and automatic collision avoidance decision-making for ships, the decision-making process is fully recognized. In this paper, the model of ship dynamic domain are adopted and a series of simulation studies are made. The safe distance of approach (SDA) is determined by ship dynamic domain. Then ship automatic collision avoidance procedure is established to controlling course alteration for collision avoidance. Experimental results show that ship dynamic domain is suitable to collision avoidance. The key factor that leads to the in validation is the CRI and course alteration. Based on the seagoing experience and simulation, the decision-making for collision avoidance in three encounter situations is accurate enough for this application. The results provide a reference that compute and display the ship parameters fast and accurately to decision-making process of ship collision avoidance.",
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