The development of machinelearning provides a strong research foundation for the field of brain science. Compared with traditional research methods, the strategy based on machinelearning is more suitable for the big...
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machinelearning models are usually based on a single dataset and a single architecture approach. But this approach falls behind in many practical scenarios. Many techniques such as boosting and bagging have been deve...
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Autonomous Underwater Vehicle (AUV) plays an important role in plenty of fields. It is a challenging task to design a high-performance formation controller for AUVs. In this paper, a formation control policy of dual u...
Autonomous Underwater Vehicle (AUV) plays an important role in plenty of fields. It is a challenging task to design a high-performance formation controller for AUVs. In this paper, a formation control policy of dual underwater vehicles based on the deep reinforcement learning method Deep Deterministic Policy Gradient method (DDPG) is proposed. The goal of our scenario is that the back AUV follows the front AUV at a certain safe distance. The policy trains the speed and direction of the back AUV, meanwhile, the customized reward function is used to ensure that the distance between the back AUV and the front AUV is within the safe distance range, and minimize the lateral deviation. The simulation results show the effectiveness of the deep reinforcement learning method in AUV formation control.
Firstly, this paper studies the characteristics of the information environment in the tactical environment in the information age, and elaborates the definition, principles, characteristics, supporting technology and ...
Firstly, this paper studies the characteristics of the information environment in the tactical environment in the information age, and elaborates the definition, principles, characteristics, supporting technology andapplication of zero trust technology; secondly, it summarizes the development and evolution of the U.S. military's tactical cloud, service model, and the proficiency test raises the problem; once again, it analyzes the main structure andapplication scenarios of the Zscaler tactical cloud solution based on zero trust, and analyzes (Zscaler Private Access) and ZIA (Zscaler Internet Access, Zscaler Internet Access) solution, and summarized its characteristics and advantages; finally, put forward the enlightenment and suggestions based on the zero-trust tactical cloud for the future development of our army’s network information system.
Diabetes is a major metabolic disease that can seriously affect the whole human body. Nowadays, diabetes has become a common disease to mankind from young to old. The number of reported diabetic patients is escalating...
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License plate is the "ID card" of a vehicle, which contains the information of the owner and the vehicle. As the identification mark of the vehicle, license plate recognition is a key part of the whole intel...
License plate is the "ID card" of a vehicle, which contains the information of the owner and the vehicle. As the identification mark of the vehicle, license plate recognition is a key part of the whole intelligent transportation system. This paper uses the method based on deep learning to detect and recognize the license plate. Due to the multi-scale detection ability of SSD target detection network, this paper selects SSD target detection algorithm in the process of license plate detection, and improves the non maximum suppression algorithm. In the license plate non segmentation character recognition, the convolution neural network is used to extract the license plate features. According to the size of the license plate text, the window of the last two pooling layers in the network is improved to better retain the license plate text information, enhance the license plate character recognition ability, and improve the robustness of license plate recognition.
The neural style transfer (NST) is an important task in the computer vision area. It aims to combine the content in an image with other images and generate an image with a specific style. This technique has been appli...
The neural style transfer (NST) is an important task in the computer vision area. It aims to combine the content in an image with other images and generate an image with a specific style. This technique has been applied to many downstream image-related tasks andapplications. Recently, the NST has made great progress with Convolution Neural Network (CNN), Generative Adversarial Network (GAN), and their variants. Thus, it is necessary to make a review of current work in NST. In this review, we firstly introduce the definition of NST and different types of NST algorithms. Then, we demonstrate some commonly used datasets and some indicators to evaluate the performance of different NST models. Finally, we analyze related work of NST and summarize some potential challenges and remained problems of state-of-the-art (SOTA) researches. This review will not only provide a good reference for researchers but also provide guidelines for some novices.
The employee attendance is an important indicator to judge employees' work attitude and measure their workload, which directly impact the development of the corporation. Meanwhile, the absenteeism, referring to th...
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Missing data is a growing concern in social science research. This paper introduces novel machine-learning methods to explore imputation efficiency and its effect on missing data. The authors used the Internet and pub...
Missing data is a growing concern in social science research. This paper introduces novel machine-learning methods to explore imputation efficiency and its effect on missing data. The authors used the Internet and public service data as the test examples. The empirical results show that the method not only verified the robustness of the positive impact of Internet penetration on the public service, but also further ensured that the machine-learning imputation method greatly improved the model’s explanatory power. The panel data after machine-learning imputation with better continuity in the time trend is feasibly analyzed, which can also be analyzed using the dynamic panel model. The long-term effects of the Internet on public services were found to be significantly stronger than the short-term effects. In short, in the era of big data, machine-learning methods can effectively improve the efficiency of data utilization and imputation accuracy, and further ensure the feasibility of the model in the actual study and the robustness of the regression results.
作者：
Chinnaiyan, R.Stalin Alex, D.
Department of ISE CMR Institute of Technology Research Scholar !!!Department of CSE Bengaluru560 037 India JGI Global Campus
Data Science Department of Computer Science and Technology Bengaluru562112 India
Cardiotocography is an important process in pregnancy such as monitoring the baby. It looks at whether a child's heartbeat is healthy or not. This can also determine whether a baby's movement in the womb is no...
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