Intelligent recommendation system based on decision model of archive translation tasks
How to recruit, test, and train the intelligent recommendation system users, and how to assign the archive translation tasks to all intelligent recommendation system users according to the intelligent matching principles are still a problem that needs to be solved. With the help of proper names and terms in China's Imperial Maritime Customs archives, this manuscript aims to solve the problem. When the corresponding translation, domain or attributes of a proper name or term is known, it will be...
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How to recruit, test, and train the intelligent recommendation system users, and how to assign the archive translation tasks to all intelligent recommendation system users according to the intelligent matching principles are still a problem that needs to be solved. With the help of proper names and terms in China's Imperial Maritime Customs archives, this manuscript aims to solve the problem. When the corresponding translation, domain or attributes of a proper name or term is known, it will be...
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Artificial intelligence insights into hippocampal processing
Advances in artificial intelligence, machine learning, and deep neural networks have led to new discoveries in human and animal learning and intelligence. A recent artificial intelligence agent in the DeepMind family, muZero, can complete a variety of tasks with limited information about the world in which it is operating and with high uncertainty about features of current and future space. To perform, muZero uses only three functions that are general yet specific enough to allow learning across...
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Advances in artificial intelligence, machine learning, and deep neural networks have led to new discoveries in human and animal learning and intelligence. A recent artificial intelligence agent in the DeepMind family, muZero, can complete a variety of tasks with limited information about the world in which it is operating and with high uncertainty about features of current and future space. To perform, muZero uses only three functions that are general yet specific enough to allow learning across...
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High precision visual localization method of UAV based on feature matching
In this paper, the precision hovering problem of UAV operation is studied. Aiming at the diversity and complexity of the UAV operating environment, a high-precision visual positioning and orientation method based on image feature matching was proposed. The image feature matching based on the improved AKAZE algorithm is realized, and the optimal matching point pair screening method based on the fusion of Hamming distance and matching line angle is innovatively proposed, which greatly improves the...
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In this paper, the precision hovering problem of UAV operation is studied. Aiming at the diversity and complexity of the UAV operating environment, a high-precision visual positioning and orientation method based on image feature matching was proposed. The image feature matching based on the improved AKAZE algorithm is realized, and the optimal matching point pair screening method based on the fusion of Hamming distance and matching line angle is innovatively proposed, which greatly improves the...
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Research on the multi-granularity method of role engineering
The role-based access control model (RBAC) is an access control approach oriented to enterprise security policy, which plays a leading role in the field of access control due to its good applicability and flexibility. However, as the scale of access subjects and access objects expands, it becomes more difficult to develop a role engineering system that meets security requirements. Particle size calculation can reduce or improve the particle size of the problem and improve efficiency on the...
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The role-based access control model (RBAC) is an access control approach oriented to enterprise security policy, which plays a leading role in the field of access control due to its good applicability and flexibility. However, as the scale of access subjects and access objects expands, it becomes more difficult to develop a role engineering system that meets security requirements. Particle size calculation can reduce or improve the particle size of the problem and improve efficiency on the...
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A multi-frame network model for predicting seizure based on sEEG and iEEG data
INTRODUCTION: Analysis and prediction of seizures by processing the EEG signals could assist doctors in accurate diagnosis and improve the quality of the patient's life with epilepsy. Nowadays, seizure prediction models based on deep learning have become one of the most popular topics in seizure studies, and many models have been presented. However, the prediction results are strongly related to the various complicated pre-processing strategies of models, and cannot be directly applied to raw...
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INTRODUCTION: Analysis and prediction of seizures by processing the EEG signals could assist doctors in accurate diagnosis and improve the quality of the patient's life with epilepsy. Nowadays, seizure prediction models based on deep learning have become one of the most popular topics in seizure studies, and many models have been presented. However, the prediction results are strongly related to the various complicated pre-processing strategies of models, and cannot be directly applied to raw...
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GAPCNN with HyPar: Global Average Pooling convolutional neural network with novel NNLU activation function and HYBRID parallelism
With the increasing demand for deep learning in the last few years, CNNs have been widely used in many applications and have gained interest in classification, regression, and image recognition tasks. The training of these deep neural networks is compute-intensive and takes days or even weeks to train the model from scratch. The compute-intensive nature of these deep neural networks sometimes limits the practical implementation of CNNs in real-time applications. Therefore, the computational...
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With the increasing demand for deep learning in the last few years, CNNs have been widely used in many applications and have gained interest in classification, regression, and image recognition tasks. The training of these deep neural networks is compute-intensive and takes days or even weeks to train the model from scratch. The compute-intensive nature of these deep neural networks sometimes limits the practical implementation of CNNs in real-time applications. Therefore, the computational...
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Neuronal and behavioral affective perceptions of human and naturalness-reduced emotional prosodies
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Dynamic control of eye-head gaze shifts by a spiking neural network model of the superior colliculus
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Brain-inspired Predictive Coding Improves the Performance of Machine Challenging Tasks
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Outer-synchronization criterions for asymmetric recurrent time-varying neural networks described by differential-algebraic system <em>via</em> data-sampling principles
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A theoretical model reveals specialized synaptic depressions and temporal frequency tuning in retinal parallel channels
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BIAS-3D: Brain inspired attentional search model fashioned after what and where/how pathways for target search in 3D environment
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Sparse measures with swarm-based pliable hidden Markov model and deep learning for EEG classification
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Production of adaptive movement patterns <em>via</em> an insect inspired spiking neural network central pattern generator
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Perineuronal nets restrict transport near the neuron surface: A coarse-grained molecular dynamics study
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Integrating ankle and hip strategies for the stabilization of upright standing: An intermittent control model
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Integrated world modeling theory expanded: Implications for the future of consciousness
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An interpretable approach for automatic aesthetic assessment of remote sensing images
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Biases in BCI experiments: Do we really need to balance stimulus properties across categories?
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