ECISER: Efficient Clip-art Image SEgmentation by Re-rasterization

Clip-art image segmentation is widely used as an essential step to solve many vision problems such as colorization and vectorization. Many of these applications not only demand accurate segmentation results, but also have little tolerance for time cost, which leads to the main challenge of this kind of segmentation. However, most existing segmentation techniques are found not sufficient for this purpose due to either their high computation cost or low accuracy. To address such issues, we propose a novel segmentation approach, ECISER, which is well-suited in this context. The basic idea of ECISER is to take advantage of the particular nature of cartoon images and connect image segmentation with aliased rasterization. Based on such relationship, a clip-art image can be quickly segmented into regions by re-rasterization of the original image and several other computationally efficient techniques developed in this paper. Experimental results show that our method achieves dramatic computational speedups over the current state-of-the-art approaches, while preserving almost the same quality of results.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

轴向磁场无铁心无刷永磁盘式电机的设计

介绍了轮用轴向磁场无铁心无刷永磁盘式电机的结构形式，探讨了这种新电机的设计特点，重点解决了电机主要尺寸确定和磁路分析计算问题，最后给出了一种磁极形状和线圈形状的优选方案。     

Method to Characterize the Air Flow and Water Removal Characteristics During Vacuum Dewatering. Part II—Analysis and Characterization

This is part II of a study reported earlier on a method to characterize the air flow and water removal characteristics during vacuum dewatering. This article presents experimental data and analysis of results from the use of a cyclically actuated vacuum dewatering device for removing moisture from wetted porous materials such as paper with the intermittent application of vacuum and accompanying air flow though the material. Results presented include sheet moisture content as a function of residence time and hence water removal rate under a variety of process conditions. Also, experimental results on air flow through the wet porous structure and hence the role and importance of air flow during vacuum dewatering are presented. Vacuum dewatering process conditions include exit solids content between 11 and 20% solid under applied vacuum conditions of 13.5 to 67.7 kPa (4 to 20 in. Hg). Regression analysis indicated that the exit sheet moisture content exhibited a nonlinear relationship with residence time with exit solids reaching a plateau after a certain residence time. Final moisture content correlated linearly with the average overall flow rate of air through the paper sample and the basis weight of the material.     

Cluster analysis in industrial market segmentation through artificial neural network

Market segmentation has commonly applied cluster analysis. This study intends to make the comparison of conventional two-stage method with proposed two-stage method through the simulated data. The proposed two-stage method is the combination of self-organizing feature maps and K-means method. The simulation results show that the proposed scheme is better than the conventional two-stage method based on the rate of misclassification.     

A Novel Segmentation and Feedback Model for Resolving Contention in Optical Burst Switching

A novel segmentation and feedback model (SFM) applied to resolve contention is proposed. Simulation and performance analyses show that the SFM effectively avoids contentions in optical burst switching (OBS). The long delay time of deflection routing and the immature technology of wavelength converters and optical buffers are not deployed in the SFM. The SFM does not only realize fast switching but also allows preemption by higher priority bursts.     

强度型光纤传感器的信号检测系统

本文阐述了一种可提高强度型光纤传感器测量精度的检测系统。该系统利用同一检测电路交替检测信号、参考通道的输出信号，并将信号、参考两通道的检测结果相除，从而消除了因发光二极管光源波动及检测电路系统不稳定所带来的误差。采用同步相关技术抑制了噪声，提高了输出信噪比。实验证明，当时间常数ＲＣ为０．０５Ｓ时，采用该检测系统可获得优于千分之一的零点稳定性和优于２×１０３的输出信噪比。     

光盘用光学头物镜性能的综合评估

论述了采用波象差均方根、点扩展函数、光学传递函数对高次旋转对称非球面光学头物镜性能进行综合评估的方法。作者在正则坐标理论基础〔１〕上编制了光学头物镜性能综合评估软件。给出了评估实例。     

提升机液压站及制动系统故障分析

通过对TE121液压站及制动系统常见的故障分析,提出解决方案。     

Learning-based dynamic coupling of discrete and continuous trackers

We present a data-driven dynamic coupling between discrete and continuous methods for tracking objects of high dofs, which overcomes the limitations of previous techniques. In our approach, two trackers work in parallel, and the coupling between them is based on the tracking error. We use a model-based continuous method to achieve accurate results and, in cases of failure, we re-initialize the model using our discrete tracker. This method maintains the accuracy of a more tightly coupled system, while increasing its efficiency. At any given frame, our discrete tracker uses the current and several previous frames to search into a database for the best matching solution. For improved robustness, object configuration sequences, rather than single configurations, are stored in the database. We apply our framework to the problem of 3D hand tracking from image sequences and the discrimination between fingerspelling and continuous signs in American Sign Language.