AIMC Topic: Neural Networks, Computer

Clear Filters Showing 24681 to 24690 of 31376 articles

Nonlinear autoregressive neural networks with external inputs for forecasting of typhoon inundation level.

Environmental monitoring and assessment
Accurate inundation level forecasting during typhoon invasion is crucial for organizing response actions such as the evacuation of people from areas that could potentially flood. This paper explores the ability of nonlinear autoregressive neural netw...

Entity recognition from clinical texts via recurrent neural network.

BMC medical informatics and decision making
BACKGROUND: Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health inform...

Automatic Image-Based Plant Disease Severity Estimation Using Deep Learning.

Computational intelligence and neuroscience
Automatic and accurate estimation of disease severity is essential for food security, disease management, and yield loss prediction. Deep learning, the latest breakthrough in computer vision, is promising for fine-grained disease severity classificat...

Efficiency of rate and latency coding with respect to metabolic cost and time.

Bio Systems
Recent studies on the theoretical performance of latency and rate code in single neurons have revealed that the ultimate accuracy is affected in a nontrivial way by aspects such as the level of spontaneous activity of presynaptic neurons, amount of n...

Piecewise convexity of artificial neural networks.

Neural networks : the official journal of the International Neural Network Society
Although artificial neural networks have shown great promise in applications including computer vision and speech recognition, there remains considerable practical and theoretical difficulty in optimizing their parameters. The seemingly unreasonable ...

Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model.

Computational intelligence and neuroscience
The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (re)consolidation are un...

Maximum likelihood optimal and robust Support Vector Regression with lncosh loss function.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel and continuously differentiable convex loss function based on natural logarithm of hyperbolic cosine function, namely lncosh loss, is introduced to obtain Support Vector Regression (SVR) models which are optimal in the maximum ...

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

Medical image analysis
Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and the...

Periodicity and stability for variable-time impulsive neural networks.

Neural networks : the official journal of the International Neural Network Society
The paper considers a general neural networks model with variable-time impulses. It is shown that each solution of the system intersects with every discontinuous surface exactly once via several new well-proposed assumptions. Moreover, based on the c...

Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states.

Neural networks : the official journal of the International Neural Network Society
We propose a new value function approach for model-free reinforcement learning in Markov decision processes involving high dimensional states that addresses the issues of brittleness and intractable computational complexity, therefore rendering the v...