From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

비만아 부모의 돌봄 경험: q 방법론

Applications of machine learning to machine fault diagnosis: A review and roadmap

1D convolutional neural networks and applications: A survey

During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with alternating convolutional and subsampling layers. Deep 2D CNNs with many hidden layers and millions of parameters have the ability to learn complex objects and patterns providing that they can be trained on a massive size visual database with ground-truth labels. With a proper training, this unique ability makes them the primary tool for various engineering applications for 2D signals such as images and video frames. Yet, this may not be a viable option in numerous applications over 1D signals especially when the training data is scarce or application-specific. To address this issue, 1D CNNs have recently been proposed and immediately achieved the state-of-the-art performance levels in several applications such as personalized biomedical data classification and early diagnosis, structural health monitoring, anomaly detection and identification in power electronics and motor-fault detection. Another major advantage is that a real-time and low-cost hardware implementation is feasible due to the simple and compact configuration of 1D CNNs that perform only 1D convolutions (scalar multiplications and additions). This paper presents a comprehensive review of the general architecture and principals of 1D CNNs along with their major engineering applications, especially focused on the recent progress in this field. Their state-of-the-art performance is highlighted concluding with their unique properties. The benchmark datasets and the principal 1D CNN software used in those applications are also publically shared in a dedicated website.

1D Convolutional Neural Networks and Applications: A Survey

In this paper, An adaptive controller with an orthogonal neural network (ONN) and a third order sliding mode(TOSM) observer for robot manipulators is proposed. Firstly, the TOSM observer is designed to observe joint velocities. Then, the ONN is designed to compensate robot dynamic uncertainties on line inside a computed torque control structure. Therefore, the proposed controller allows only position measurements due to the TOSM observer and achieve highly accurate trajectory tracking performance due to the ONN’s uncertainty compensation. Finally, computer simulation for a 2-DOF manipulator is performed to show verify the effectiveness of the proposed controller. 

/pdf/an-adaptive-controller-with-an-orthogonal-neural-network-and-1bnf3yko4z.pdf

An Adaptive Controller with An Orthogonal Neural Network and A Third Order Sliding Mode Observer for Robot Manipulators

A calibration method of a robot having the joint rigidity parameter for the location accuracy improvement is provided to improve the precision of the robot by calculating the compliance parameter and the link parameter. A calibration method of a robot having the joint rigidity parameter for the location accuracy improvement comprises: a step of modeling to the joint rigidity parameter relative to the robot weight with the joint stiffness parameter in consideration of the rigidity and load of a robot(10) end part(11) articulated axle; and a step of calculating the compliance matrices of the articulated axle and compensating. Through the calibration method of the robot considering the rigidity parameter, the positional precision of the robot can be improved. The compliance parameter of the articulated axle and the link parameter due to the droops are the difference of the place value in which the measured place value and the link parameter are calculated.

https://www.koreascience.or.kr:443/article/JAKO200817154053559.pdf

Robot Calibration with Joint Stiffness Parameters for the Enhanced Positioning Accuracy

In this study, a manipulator calibration algorithm is suggested to decrease the positional errors of an industrial robotic manipulator using a genetic algorithm to select optimal measurement poses. First, a genetic algorithm based on the observability index is used for the selection of optimal measurement poses. By employing the selected optimal poses, conventional kinematic calibration is used to identify the geometric errors of the robot. Finally, to further improve the positional accuracy of the robot, compliance errors are compensated by a radial basis function neural network based on effective torques. The proposed method provides a novel and effective way to select optimal measurement poses for the calibration process using a genetic algorithm and enhances the accuracy of the robot manipulators by constructing a relationship between the effective torque and the compliance errors using a radial basis function. The results of the experimental calibration and validation processes carried out on a YS100 robot show the effectiveness of the proposed method in comparison with the other calibration approaches.

/pdf/a-new-manipulator-calibration-method-for-the-identification-2ss5isvr.pdf

A New Manipulator Calibration Method for the Identification of Kinematic and Compliance Errors Using Optimal Pose Selection

An H2 filter is derived for time delay systems, where there are time delay terms in the state and in the output. A method to compute the H2 norm of time delay systems is proposed. Based on the H2 norm computation method, an H2 filter design is formulated as a nonlinear optimization problem.

/pdf/h2-filter-for-time-delay-systems-4wlovdw6c9.pdf

H2 Filter for Time Delay Systems

To maintain the safe operation and acceptable performance of robot manipulators when faults occur inside the system, fault-tolerant control must deal differently uncertainties and disturbances, especially with the occurrence of loss-effective faults. Therefore, in this paper, an active fault-tolerant control for robot manipulators based on the combination of a novel finite-time synchronous fast terminal sliding mode control and extended state observer is proposed. Due to the internal constraints of the synchronization technique, the position error at each actuator simultaneously approaches zero and tends to be equal. Therefore, the proposed controller can suppress the effects of faults and guarantee the acceptable performance of robot manipulators when faults occur. First, an extended state observer is designed to estimate the lumped uncertainties, disturbance and faults. Then, the information from the observer is used to combine with the main novel synchronous fast terminal sliding mode controller as a compensator. By combining the merits of the observer compensation, sliding mode and synchronization technique, the proposed fault-tolerant controller is able to deal with uncertainties and disturbances in normal operation mode and reduce the effects of faults in case faults occur, especially in the occurrence of loss-effective faults. Finally, the enhanced safety, reality and effectiveness of the proposed fault-tolerant control are evaluated through the control of a 3-DOF robot manipulator in both a simulated environment and experiment.

/pdf/an-active-fault-tolerant-control-based-on-synchronous-fast-2x6yvlj2.pdf

Hee-Jun Kang

Papers

An Adaptive Controller with An Orthogonal Neural Network and A Third Order Sliding Mode Observer for Robot Manipulators

Robot Calibration with Joint Stiffness Parameters for the Enhanced Positioning Accuracy

A New Manipulator Calibration Method for the Identification of Kinematic and Compliance Errors Using Optimal Pose Selection

H2 Filter for Time Delay Systems

An Active Fault-Tolerant Control Based on Synchronous Fast Terminal Sliding Mode for a Robot Manipulator